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You searched for subject:(neuromorphic). Showing records 1 – 30 of 199 total matches.

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1. Kim, Yongtae. Energy Efficient and Error Resilient Neuromorphic Computing in VLSI.

Degree: 2013, Texas Digital Library

 Realization of the conventional Von Neumann architecture faces increasing challenges due to growing process variations, device reliability and power consumption. As an appealing architectural solution,… (more)

Subjects/Keywords: neuromorphic computing

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APA (6th Edition):

Kim, Y. (2013). Energy Efficient and Error Resilient Neuromorphic Computing in VLSI. (Thesis). Texas Digital Library. Retrieved from http://hdl.handle.net/1969; http://hdl.handle.net/2249.1/66614

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Kim, Yongtae. “Energy Efficient and Error Resilient Neuromorphic Computing in VLSI.” 2013. Thesis, Texas Digital Library. Accessed November 18, 2019. http://hdl.handle.net/1969; http://hdl.handle.net/2249.1/66614.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Kim, Yongtae. “Energy Efficient and Error Resilient Neuromorphic Computing in VLSI.” 2013. Web. 18 Nov 2019.

Vancouver:

Kim Y. Energy Efficient and Error Resilient Neuromorphic Computing in VLSI. [Internet] [Thesis]. Texas Digital Library; 2013. [cited 2019 Nov 18]. Available from: http://hdl.handle.net/1969; http://hdl.handle.net/2249.1/66614.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Kim Y. Energy Efficient and Error Resilient Neuromorphic Computing in VLSI. [Thesis]. Texas Digital Library; 2013. Available from: http://hdl.handle.net/1969; http://hdl.handle.net/2249.1/66614

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Georgia Tech

2. Shank, Joshua. Memristive devices for neuromorphic computing applications.

Degree: PhD, Electrical and Computer Engineering, 2016, Georgia Tech

 The performance of digital computers has begun to saturate due to material, size, and power limitations. In addition to solving these dilemmas, new computing paradigms… (more)

Subjects/Keywords: Memristor; Neuromorphic

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APA (6th Edition):

Shank, J. (2016). Memristive devices for neuromorphic computing applications. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/55687

Chicago Manual of Style (16th Edition):

Shank, Joshua. “Memristive devices for neuromorphic computing applications.” 2016. Doctoral Dissertation, Georgia Tech. Accessed November 18, 2019. http://hdl.handle.net/1853/55687.

MLA Handbook (7th Edition):

Shank, Joshua. “Memristive devices for neuromorphic computing applications.” 2016. Web. 18 Nov 2019.

Vancouver:

Shank J. Memristive devices for neuromorphic computing applications. [Internet] [Doctoral dissertation]. Georgia Tech; 2016. [cited 2019 Nov 18]. Available from: http://hdl.handle.net/1853/55687.

Council of Science Editors:

Shank J. Memristive devices for neuromorphic computing applications. [Doctoral Dissertation]. Georgia Tech; 2016. Available from: http://hdl.handle.net/1853/55687


Universiteit Utrecht

3. Keemink, S.W. Mimicking synaptic plasticity in memristive neuromorphic systems.

Degree: 2012, Universiteit Utrecht

 Development of artificial intelligence has been disappointing in many aspects, and has been severely limited by the basic architecture of computers. The new field of… (more)

Subjects/Keywords: Neuromorphic engineering; memristance; synapses; plasticity

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APA (6th Edition):

Keemink, S. W. (2012). Mimicking synaptic plasticity in memristive neuromorphic systems. (Masters Thesis). Universiteit Utrecht. Retrieved from http://dspace.library.uu.nl:8080/handle/1874/254240

Chicago Manual of Style (16th Edition):

Keemink, S W. “Mimicking synaptic plasticity in memristive neuromorphic systems.” 2012. Masters Thesis, Universiteit Utrecht. Accessed November 18, 2019. http://dspace.library.uu.nl:8080/handle/1874/254240.

MLA Handbook (7th Edition):

Keemink, S W. “Mimicking synaptic plasticity in memristive neuromorphic systems.” 2012. Web. 18 Nov 2019.

Vancouver:

Keemink SW. Mimicking synaptic plasticity in memristive neuromorphic systems. [Internet] [Masters thesis]. Universiteit Utrecht; 2012. [cited 2019 Nov 18]. Available from: http://dspace.library.uu.nl:8080/handle/1874/254240.

Council of Science Editors:

Keemink SW. Mimicking synaptic plasticity in memristive neuromorphic systems. [Masters Thesis]. Universiteit Utrecht; 2012. Available from: http://dspace.library.uu.nl:8080/handle/1874/254240


University of Southern California

4. Joshi, Jonathan R. Plasticity in CMOS neuromorphic circuits.

Degree: PhD, Electrical Engineering, 2013, University of Southern California

 A thesis exploring first-order in-silico modeling of changes (plasticity) in biological neurons is presented. In biological neural networks there is an intricate feedback relationship between… (more)

Subjects/Keywords: circuits; CMOS; neuromorphic; plasticity; structural

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APA (6th Edition):

Joshi, J. R. (2013). Plasticity in CMOS neuromorphic circuits. (Doctoral Dissertation). University of Southern California. Retrieved from http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/219476/rec/5078

Chicago Manual of Style (16th Edition):

Joshi, Jonathan R. “Plasticity in CMOS neuromorphic circuits.” 2013. Doctoral Dissertation, University of Southern California. Accessed November 18, 2019. http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/219476/rec/5078.

MLA Handbook (7th Edition):

Joshi, Jonathan R. “Plasticity in CMOS neuromorphic circuits.” 2013. Web. 18 Nov 2019.

Vancouver:

Joshi JR. Plasticity in CMOS neuromorphic circuits. [Internet] [Doctoral dissertation]. University of Southern California; 2013. [cited 2019 Nov 18]. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/219476/rec/5078.

Council of Science Editors:

Joshi JR. Plasticity in CMOS neuromorphic circuits. [Doctoral Dissertation]. University of Southern California; 2013. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/219476/rec/5078

5. Kimura, Mutsumi. Study on Neuromorphic Systems using Thin-Film Devices : 薄膜デバイスを用いたニューロモーフィックシステムに関する研究; ハクマク デバイス オ モチイタ ニューロ モーフィック システム ニ カンスル ケンキュウ.

Degree: 博士(理学), 2018, Nara Institute of Science and Technology / 奈良先端科学技術大学院大学

Subjects/Keywords: neuromorphic system

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APA (6th Edition):

Kimura, M. (2018). Study on Neuromorphic Systems using Thin-Film Devices : 薄膜デバイスを用いたニューロモーフィックシステムに関する研究; ハクマク デバイス オ モチイタ ニューロ モーフィック システム ニ カンスル ケンキュウ. (Thesis). Nara Institute of Science and Technology / 奈良先端科学技術大学院大学. Retrieved from http://hdl.handle.net/10061/12502

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Kimura, Mutsumi. “Study on Neuromorphic Systems using Thin-Film Devices : 薄膜デバイスを用いたニューロモーフィックシステムに関する研究; ハクマク デバイス オ モチイタ ニューロ モーフィック システム ニ カンスル ケンキュウ.” 2018. Thesis, Nara Institute of Science and Technology / 奈良先端科学技術大学院大学. Accessed November 18, 2019. http://hdl.handle.net/10061/12502.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Kimura, Mutsumi. “Study on Neuromorphic Systems using Thin-Film Devices : 薄膜デバイスを用いたニューロモーフィックシステムに関する研究; ハクマク デバイス オ モチイタ ニューロ モーフィック システム ニ カンスル ケンキュウ.” 2018. Web. 18 Nov 2019.

Vancouver:

Kimura M. Study on Neuromorphic Systems using Thin-Film Devices : 薄膜デバイスを用いたニューロモーフィックシステムに関する研究; ハクマク デバイス オ モチイタ ニューロ モーフィック システム ニ カンスル ケンキュウ. [Internet] [Thesis]. Nara Institute of Science and Technology / 奈良先端科学技術大学院大学; 2018. [cited 2019 Nov 18]. Available from: http://hdl.handle.net/10061/12502.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Kimura M. Study on Neuromorphic Systems using Thin-Film Devices : 薄膜デバイスを用いたニューロモーフィックシステムに関する研究; ハクマク デバイス オ モチイタ ニューロ モーフィック システム ニ カンスル ケンキュウ. [Thesis]. Nara Institute of Science and Technology / 奈良先端科学技術大学院大学; 2018. Available from: http://hdl.handle.net/10061/12502

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


University of Tennessee – Knoxville

6. Weiss, Ryan John. Analog Axon Hillock Neuron Design for Memristive Neuromorphic Systems.

Degree: MS, Electrical Engineering, 2017, University of Tennessee – Knoxville

Neuromorphic electronics studies the physical realization of neural networks in discrete circuit components. Hardware implementations of neural networks take advantage of highly parallelized computing power… (more)

Subjects/Keywords: Neuromorphic; Neuron; Memristor; Analog

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APA (6th Edition):

Weiss, R. J. (2017). Analog Axon Hillock Neuron Design for Memristive Neuromorphic Systems. (Thesis). University of Tennessee – Knoxville. Retrieved from https://trace.tennessee.edu/utk_gradthes/4986

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Weiss, Ryan John. “Analog Axon Hillock Neuron Design for Memristive Neuromorphic Systems.” 2017. Thesis, University of Tennessee – Knoxville. Accessed November 18, 2019. https://trace.tennessee.edu/utk_gradthes/4986.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Weiss, Ryan John. “Analog Axon Hillock Neuron Design for Memristive Neuromorphic Systems.” 2017. Web. 18 Nov 2019.

Vancouver:

Weiss RJ. Analog Axon Hillock Neuron Design for Memristive Neuromorphic Systems. [Internet] [Thesis]. University of Tennessee – Knoxville; 2017. [cited 2019 Nov 18]. Available from: https://trace.tennessee.edu/utk_gradthes/4986.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Weiss RJ. Analog Axon Hillock Neuron Design for Memristive Neuromorphic Systems. [Thesis]. University of Tennessee – Knoxville; 2017. Available from: https://trace.tennessee.edu/utk_gradthes/4986

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


University of Minnesota

7. Tagare, Deepak Kumar. A Multicore Neuromorphic Chip Design Using Multilevel Synapses in 65nm Standard CMOS Technology.

Degree: MS, Electrical Engineering, 2015, University of Minnesota

Neuromorphic research community is focused on designing a hardware which is as efficient as biological brain in terms of performance, power and area. It opens… (more)

Subjects/Keywords: Eflash; Neuromorphic engineering; Non-volatile

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APA (6th Edition):

Tagare, D. K. (2015). A Multicore Neuromorphic Chip Design Using Multilevel Synapses in 65nm Standard CMOS Technology. (Masters Thesis). University of Minnesota. Retrieved from http://hdl.handle.net/11299/190620

Chicago Manual of Style (16th Edition):

Tagare, Deepak Kumar. “A Multicore Neuromorphic Chip Design Using Multilevel Synapses in 65nm Standard CMOS Technology.” 2015. Masters Thesis, University of Minnesota. Accessed November 18, 2019. http://hdl.handle.net/11299/190620.

MLA Handbook (7th Edition):

Tagare, Deepak Kumar. “A Multicore Neuromorphic Chip Design Using Multilevel Synapses in 65nm Standard CMOS Technology.” 2015. Web. 18 Nov 2019.

Vancouver:

Tagare DK. A Multicore Neuromorphic Chip Design Using Multilevel Synapses in 65nm Standard CMOS Technology. [Internet] [Masters thesis]. University of Minnesota; 2015. [cited 2019 Nov 18]. Available from: http://hdl.handle.net/11299/190620.

Council of Science Editors:

Tagare DK. A Multicore Neuromorphic Chip Design Using Multilevel Synapses in 65nm Standard CMOS Technology. [Masters Thesis]. University of Minnesota; 2015. Available from: http://hdl.handle.net/11299/190620


Texas A&M University

8. Kim, Yongtae. Energy Efficient and Error Resilient Neuromorphic Computing in VLSI.

Degree: 2013, Texas A&M University

 Realization of the conventional Von Neumann architecture faces increasing challenges due to growing process variations, device reliability and power consumption. As an appealing architectural solution,… (more)

Subjects/Keywords: neuromorphic computing; approximate computing; neuromorphic processor; approximate adder; approximate comparator

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APA (6th Edition):

Kim, Y. (2013). Energy Efficient and Error Resilient Neuromorphic Computing in VLSI. (Thesis). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/151721

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Kim, Yongtae. “Energy Efficient and Error Resilient Neuromorphic Computing in VLSI.” 2013. Thesis, Texas A&M University. Accessed November 18, 2019. http://hdl.handle.net/1969.1/151721.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Kim, Yongtae. “Energy Efficient and Error Resilient Neuromorphic Computing in VLSI.” 2013. Web. 18 Nov 2019.

Vancouver:

Kim Y. Energy Efficient and Error Resilient Neuromorphic Computing in VLSI. [Internet] [Thesis]. Texas A&M University; 2013. [cited 2019 Nov 18]. Available from: http://hdl.handle.net/1969.1/151721.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Kim Y. Energy Efficient and Error Resilient Neuromorphic Computing in VLSI. [Thesis]. Texas A&M University; 2013. Available from: http://hdl.handle.net/1969.1/151721

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

9. Nawrocki, Robert A. Fabrication And Application Of A Polymer Neuromorphic Circuitry Based On Polymer Memristive Devices And Polymer Transistors.

Degree: PhD, Engineering, 2014, U of Denver

Neuromorphic engineering is a discipline that aims to address the shortcomings of today's serial computers, namely large power consumption, susceptibility to physical damage, as… (more)

Subjects/Keywords: Memristive Devices; Memristors; Neuromorphic Engineering; Organic Electronics

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APA (6th Edition):

Nawrocki, R. A. (2014). Fabrication And Application Of A Polymer Neuromorphic Circuitry Based On Polymer Memristive Devices And Polymer Transistors. (Doctoral Dissertation). U of Denver. Retrieved from https://digitalcommons.du.edu/etd/470

Chicago Manual of Style (16th Edition):

Nawrocki, Robert A. “Fabrication And Application Of A Polymer Neuromorphic Circuitry Based On Polymer Memristive Devices And Polymer Transistors.” 2014. Doctoral Dissertation, U of Denver. Accessed November 18, 2019. https://digitalcommons.du.edu/etd/470.

MLA Handbook (7th Edition):

Nawrocki, Robert A. “Fabrication And Application Of A Polymer Neuromorphic Circuitry Based On Polymer Memristive Devices And Polymer Transistors.” 2014. Web. 18 Nov 2019.

Vancouver:

Nawrocki RA. Fabrication And Application Of A Polymer Neuromorphic Circuitry Based On Polymer Memristive Devices And Polymer Transistors. [Internet] [Doctoral dissertation]. U of Denver; 2014. [cited 2019 Nov 18]. Available from: https://digitalcommons.du.edu/etd/470.

Council of Science Editors:

Nawrocki RA. Fabrication And Application Of A Polymer Neuromorphic Circuitry Based On Polymer Memristive Devices And Polymer Transistors. [Doctoral Dissertation]. U of Denver; 2014. Available from: https://digitalcommons.du.edu/etd/470


Texas A&M University

10. Bashaireh, Ahmad. Design Robustness Analysis of Neuromorphic Circuits.

Degree: 2014, Texas A&M University

 Conventional Von Neumann architecture faces significant challenges as the device dimensions are scaled down. Power consumption and device reliability have become major concerns. Therefore, new… (more)

Subjects/Keywords: Neuromorphic Circuits; Circuit Analysis; Character Recognition

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APA (6th Edition):

Bashaireh, A. (2014). Design Robustness Analysis of Neuromorphic Circuits. (Thesis). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/152828

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Bashaireh, Ahmad. “Design Robustness Analysis of Neuromorphic Circuits.” 2014. Thesis, Texas A&M University. Accessed November 18, 2019. http://hdl.handle.net/1969.1/152828.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Bashaireh, Ahmad. “Design Robustness Analysis of Neuromorphic Circuits.” 2014. Web. 18 Nov 2019.

Vancouver:

Bashaireh A. Design Robustness Analysis of Neuromorphic Circuits. [Internet] [Thesis]. Texas A&M University; 2014. [cited 2019 Nov 18]. Available from: http://hdl.handle.net/1969.1/152828.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Bashaireh A. Design Robustness Analysis of Neuromorphic Circuits. [Thesis]. Texas A&M University; 2014. Available from: http://hdl.handle.net/1969.1/152828

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


University of Exeter

11. Hosseini, Peiman. Phase-change and carbon based materials for advanced memory and computing devices.

Degree: PhD, 2013, University of Exeter

 The aggressive scaling of CMOS technology, to reduce device size while also increasing device performance, has reached a point where continuing improvement is becoming increasingly… (more)

Subjects/Keywords: 621.3815; phase change computation neuron neuromorphic

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APA (6th Edition):

Hosseini, P. (2013). Phase-change and carbon based materials for advanced memory and computing devices. (Doctoral Dissertation). University of Exeter. Retrieved from http://hdl.handle.net/10871/10122

Chicago Manual of Style (16th Edition):

Hosseini, Peiman. “Phase-change and carbon based materials for advanced memory and computing devices.” 2013. Doctoral Dissertation, University of Exeter. Accessed November 18, 2019. http://hdl.handle.net/10871/10122.

MLA Handbook (7th Edition):

Hosseini, Peiman. “Phase-change and carbon based materials for advanced memory and computing devices.” 2013. Web. 18 Nov 2019.

Vancouver:

Hosseini P. Phase-change and carbon based materials for advanced memory and computing devices. [Internet] [Doctoral dissertation]. University of Exeter; 2013. [cited 2019 Nov 18]. Available from: http://hdl.handle.net/10871/10122.

Council of Science Editors:

Hosseini P. Phase-change and carbon based materials for advanced memory and computing devices. [Doctoral Dissertation]. University of Exeter; 2013. Available from: http://hdl.handle.net/10871/10122


University of Southern California

12. Tseng, Ko-Chung. Neuromorphic motion sensing circuits in a silicon retina.

Degree: PhD, Electrical Engineering, 2012, University of Southern California

 In the biological retina, the feedback and lateral pathways among retinal neurons construct a complicated network that contributes to motion sensing in the retina. When… (more)

Subjects/Keywords: silicon retina; neuromorphic circuit; motion detection

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APA (6th Edition):

Tseng, K. (2012). Neuromorphic motion sensing circuits in a silicon retina. (Doctoral Dissertation). University of Southern California. Retrieved from http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/99615/rec/4374

Chicago Manual of Style (16th Edition):

Tseng, Ko-Chung. “Neuromorphic motion sensing circuits in a silicon retina.” 2012. Doctoral Dissertation, University of Southern California. Accessed November 18, 2019. http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/99615/rec/4374.

MLA Handbook (7th Edition):

Tseng, Ko-Chung. “Neuromorphic motion sensing circuits in a silicon retina.” 2012. Web. 18 Nov 2019.

Vancouver:

Tseng K. Neuromorphic motion sensing circuits in a silicon retina. [Internet] [Doctoral dissertation]. University of Southern California; 2012. [cited 2019 Nov 18]. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/99615/rec/4374.

Council of Science Editors:

Tseng K. Neuromorphic motion sensing circuits in a silicon retina. [Doctoral Dissertation]. University of Southern California; 2012. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/99615/rec/4374


University of Manchester

13. Rast, Alexander Douglas. Scalable Event-Driven Modelling Architectures for Neuromimetic Hardware.

Degree: 2011, University of Manchester

 Neural networks present a fundamentally different model of computation fromthe conventional sequential digital model. Dedicated hardware may thus be moresuitable for executing them. Given that… (more)

Subjects/Keywords: Event-Driven; Neural; Hardware; Neuromimetic; Neuromorphic; Cognitive

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APA (6th Edition):

Rast, A. D. (2011). Scalable Event-Driven Modelling Architectures for Neuromimetic Hardware. (Doctoral Dissertation). University of Manchester. Retrieved from http://www.manchester.ac.uk/escholar/uk-ac-man-scw:111900

Chicago Manual of Style (16th Edition):

Rast, Alexander Douglas. “Scalable Event-Driven Modelling Architectures for Neuromimetic Hardware.” 2011. Doctoral Dissertation, University of Manchester. Accessed November 18, 2019. http://www.manchester.ac.uk/escholar/uk-ac-man-scw:111900.

MLA Handbook (7th Edition):

Rast, Alexander Douglas. “Scalable Event-Driven Modelling Architectures for Neuromimetic Hardware.” 2011. Web. 18 Nov 2019.

Vancouver:

Rast AD. Scalable Event-Driven Modelling Architectures for Neuromimetic Hardware. [Internet] [Doctoral dissertation]. University of Manchester; 2011. [cited 2019 Nov 18]. Available from: http://www.manchester.ac.uk/escholar/uk-ac-man-scw:111900.

Council of Science Editors:

Rast AD. Scalable Event-Driven Modelling Architectures for Neuromimetic Hardware. [Doctoral Dissertation]. University of Manchester; 2011. Available from: http://www.manchester.ac.uk/escholar/uk-ac-man-scw:111900


Georgia Tech

14. Fair, Kaitlin Lindsay. A biologically plausible sparse approximation solver on neuromorphic hardware.

Degree: PhD, Electrical and Computer Engineering, 2017, Georgia Tech

 We develop a novel design methodology to map the biologically plausible Locally Competitive Algorithm (LCA) to the brain-inspired TrueNorth chip to solve for the sparse… (more)

Subjects/Keywords: Neuromorphic; Bio-inspired; TrueNorth; Sparsity; Sparse approximation

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APA (6th Edition):

Fair, K. L. (2017). A biologically plausible sparse approximation solver on neuromorphic hardware. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/59782

Chicago Manual of Style (16th Edition):

Fair, Kaitlin Lindsay. “A biologically plausible sparse approximation solver on neuromorphic hardware.” 2017. Doctoral Dissertation, Georgia Tech. Accessed November 18, 2019. http://hdl.handle.net/1853/59782.

MLA Handbook (7th Edition):

Fair, Kaitlin Lindsay. “A biologically plausible sparse approximation solver on neuromorphic hardware.” 2017. Web. 18 Nov 2019.

Vancouver:

Fair KL. A biologically plausible sparse approximation solver on neuromorphic hardware. [Internet] [Doctoral dissertation]. Georgia Tech; 2017. [cited 2019 Nov 18]. Available from: http://hdl.handle.net/1853/59782.

Council of Science Editors:

Fair KL. A biologically plausible sparse approximation solver on neuromorphic hardware. [Doctoral Dissertation]. Georgia Tech; 2017. Available from: http://hdl.handle.net/1853/59782


Georgia Tech

15. Ku, Bon Woong. Physical Design Solutions for 3D ICs and their Neuromorphic Applications.

Degree: PhD, Electrical and Computer Engineering, 2019, Georgia Tech

 The wafer-level 3D integration including face-to-face (F2F) and monolithic 3D (M3D) technologies has been featured as a promising innovation to succeed the horizontal device scaling… (more)

Subjects/Keywords: Physical Design Solutions; 3D ICs; Neuromorphic Processor

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APA (6th Edition):

Ku, B. W. (2019). Physical Design Solutions for 3D ICs and their Neuromorphic Applications. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/61227

Chicago Manual of Style (16th Edition):

Ku, Bon Woong. “Physical Design Solutions for 3D ICs and their Neuromorphic Applications.” 2019. Doctoral Dissertation, Georgia Tech. Accessed November 18, 2019. http://hdl.handle.net/1853/61227.

MLA Handbook (7th Edition):

Ku, Bon Woong. “Physical Design Solutions for 3D ICs and their Neuromorphic Applications.” 2019. Web. 18 Nov 2019.

Vancouver:

Ku BW. Physical Design Solutions for 3D ICs and their Neuromorphic Applications. [Internet] [Doctoral dissertation]. Georgia Tech; 2019. [cited 2019 Nov 18]. Available from: http://hdl.handle.net/1853/61227.

Council of Science Editors:

Ku BW. Physical Design Solutions for 3D ICs and their Neuromorphic Applications. [Doctoral Dissertation]. Georgia Tech; 2019. Available from: http://hdl.handle.net/1853/61227


Rochester Institute of Technology

16. Merkel, Cory E. Design of Neuromemristive Systems for Visual Information Processing.

Degree: PhD, Microsystems Engineering, 2015, Rochester Institute of Technology

  Neuromemristive systems (NMSs) are brain-inspired, adaptive computer architectures based on emerging resistive memory technology (memristors). NMSs adopt a mixed-signal design approach with closely-coupled memory… (more)

Subjects/Keywords: Computer vision; Machine learning; Memristor; Neuromemristive; Neuromorphic

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APA (6th Edition):

Merkel, C. E. (2015). Design of Neuromemristive Systems for Visual Information Processing. (Doctoral Dissertation). Rochester Institute of Technology. Retrieved from https://scholarworks.rit.edu/theses/8938

Chicago Manual of Style (16th Edition):

Merkel, Cory E. “Design of Neuromemristive Systems for Visual Information Processing.” 2015. Doctoral Dissertation, Rochester Institute of Technology. Accessed November 18, 2019. https://scholarworks.rit.edu/theses/8938.

MLA Handbook (7th Edition):

Merkel, Cory E. “Design of Neuromemristive Systems for Visual Information Processing.” 2015. Web. 18 Nov 2019.

Vancouver:

Merkel CE. Design of Neuromemristive Systems for Visual Information Processing. [Internet] [Doctoral dissertation]. Rochester Institute of Technology; 2015. [cited 2019 Nov 18]. Available from: https://scholarworks.rit.edu/theses/8938.

Council of Science Editors:

Merkel CE. Design of Neuromemristive Systems for Visual Information Processing. [Doctoral Dissertation]. Rochester Institute of Technology; 2015. Available from: https://scholarworks.rit.edu/theses/8938


Rochester Institute of Technology

17. Soltiz, Michael. Hardware neuromorphic learning systems utilizing memristive devices.

Degree: Computer Engineering, 2012, Rochester Institute of Technology

 As the efficiency of neuromorphic systems improves, biologically-inspired learning techniques are becoming more and more appealing for various computing applications, ranging from pattern and character… (more)

Subjects/Keywords: Memristors; Neural network; Neuromorphic; OCR; Reconfigurable logic

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APA (6th Edition):

Soltiz, M. (2012). Hardware neuromorphic learning systems utilizing memristive devices. (Thesis). Rochester Institute of Technology. Retrieved from https://scholarworks.rit.edu/theses/3174

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Soltiz, Michael. “Hardware neuromorphic learning systems utilizing memristive devices.” 2012. Thesis, Rochester Institute of Technology. Accessed November 18, 2019. https://scholarworks.rit.edu/theses/3174.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Soltiz, Michael. “Hardware neuromorphic learning systems utilizing memristive devices.” 2012. Web. 18 Nov 2019.

Vancouver:

Soltiz M. Hardware neuromorphic learning systems utilizing memristive devices. [Internet] [Thesis]. Rochester Institute of Technology; 2012. [cited 2019 Nov 18]. Available from: https://scholarworks.rit.edu/theses/3174.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Soltiz M. Hardware neuromorphic learning systems utilizing memristive devices. [Thesis]. Rochester Institute of Technology; 2012. Available from: https://scholarworks.rit.edu/theses/3174

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Rochester Institute of Technology

18. Saleh, Qutaiba Mohammed. Design of a Neuromemristive Echo State Network Architecture.

Degree: MS, Computer Engineering, 2015, Rochester Institute of Technology

  Echo state neural networks (ESNs) provide an efficient classification technique for spatiotemporal signals. The feedback connections in the ESN enable feature extraction in both… (more)

Subjects/Keywords: ESN; Memristor; Neural network; Neuromemristive; Neuromorphic

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Saleh, Q. M. (2015). Design of a Neuromemristive Echo State Network Architecture. (Masters Thesis). Rochester Institute of Technology. Retrieved from https://scholarworks.rit.edu/theses/8767

Chicago Manual of Style (16th Edition):

Saleh, Qutaiba Mohammed. “Design of a Neuromemristive Echo State Network Architecture.” 2015. Masters Thesis, Rochester Institute of Technology. Accessed November 18, 2019. https://scholarworks.rit.edu/theses/8767.

MLA Handbook (7th Edition):

Saleh, Qutaiba Mohammed. “Design of a Neuromemristive Echo State Network Architecture.” 2015. Web. 18 Nov 2019.

Vancouver:

Saleh QM. Design of a Neuromemristive Echo State Network Architecture. [Internet] [Masters thesis]. Rochester Institute of Technology; 2015. [cited 2019 Nov 18]. Available from: https://scholarworks.rit.edu/theses/8767.

Council of Science Editors:

Saleh QM. Design of a Neuromemristive Echo State Network Architecture. [Masters Thesis]. Rochester Institute of Technology; 2015. Available from: https://scholarworks.rit.edu/theses/8767

19. Marquez Alfonzo, Bicky. Reservoir computing photonique et méthodes non-linéaires de représentation de signaux complexes : Application à la prédiction de séries temporelles : Complex signal embedding and photonic reservoir Computing in time series prediction.

Degree: Docteur es, Optique et photonique, 2018, Bourgogne Franche-Comté

Les réseaux de neurones artificiels constituent des systèmes alternatifs pour effectuer des calculs complexes, ainsi que pour contribuer à l'étude des systèmes neuronaux biologiques. Ils… (more)

Subjects/Keywords: Nonlinéaire; Photonique; Neuromorphiques; Nonlinear; Photonic; Neuromorphic; 004.6

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APA (6th Edition):

Marquez Alfonzo, B. (2018). Reservoir computing photonique et méthodes non-linéaires de représentation de signaux complexes : Application à la prédiction de séries temporelles : Complex signal embedding and photonic reservoir Computing in time series prediction. (Doctoral Dissertation). Bourgogne Franche-Comté. Retrieved from http://www.theses.fr/2018UBFCD042

Chicago Manual of Style (16th Edition):

Marquez Alfonzo, Bicky. “Reservoir computing photonique et méthodes non-linéaires de représentation de signaux complexes : Application à la prédiction de séries temporelles : Complex signal embedding and photonic reservoir Computing in time series prediction.” 2018. Doctoral Dissertation, Bourgogne Franche-Comté. Accessed November 18, 2019. http://www.theses.fr/2018UBFCD042.

MLA Handbook (7th Edition):

Marquez Alfonzo, Bicky. “Reservoir computing photonique et méthodes non-linéaires de représentation de signaux complexes : Application à la prédiction de séries temporelles : Complex signal embedding and photonic reservoir Computing in time series prediction.” 2018. Web. 18 Nov 2019.

Vancouver:

Marquez Alfonzo B. Reservoir computing photonique et méthodes non-linéaires de représentation de signaux complexes : Application à la prédiction de séries temporelles : Complex signal embedding and photonic reservoir Computing in time series prediction. [Internet] [Doctoral dissertation]. Bourgogne Franche-Comté; 2018. [cited 2019 Nov 18]. Available from: http://www.theses.fr/2018UBFCD042.

Council of Science Editors:

Marquez Alfonzo B. Reservoir computing photonique et méthodes non-linéaires de représentation de signaux complexes : Application à la prédiction de séries temporelles : Complex signal embedding and photonic reservoir Computing in time series prediction. [Doctoral Dissertation]. Bourgogne Franche-Comté; 2018. Available from: http://www.theses.fr/2018UBFCD042


University of Windsor

20. Amirsoleimani, Amirali. In-Memory Computing by Using Nano-ionic Memristive Devices.

Degree: PhD, Electrical and Computer Engineering, 2017, University of Windsor

 By reaching to the CMOS scaling limitation based on the Moore’s law and due to the increasing disparity between the processing units and memory performance,… (more)

Subjects/Keywords: Computing; Logic; Memristive Systems; Memristor; Modeling; Neuromorphic

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Amirsoleimani, A. (2017). In-Memory Computing by Using Nano-ionic Memristive Devices. (Doctoral Dissertation). University of Windsor. Retrieved from https://scholar.uwindsor.ca/etd/7346

Chicago Manual of Style (16th Edition):

Amirsoleimani, Amirali. “In-Memory Computing by Using Nano-ionic Memristive Devices.” 2017. Doctoral Dissertation, University of Windsor. Accessed November 18, 2019. https://scholar.uwindsor.ca/etd/7346.

MLA Handbook (7th Edition):

Amirsoleimani, Amirali. “In-Memory Computing by Using Nano-ionic Memristive Devices.” 2017. Web. 18 Nov 2019.

Vancouver:

Amirsoleimani A. In-Memory Computing by Using Nano-ionic Memristive Devices. [Internet] [Doctoral dissertation]. University of Windsor; 2017. [cited 2019 Nov 18]. Available from: https://scholar.uwindsor.ca/etd/7346.

Council of Science Editors:

Amirsoleimani A. In-Memory Computing by Using Nano-ionic Memristive Devices. [Doctoral Dissertation]. University of Windsor; 2017. Available from: https://scholar.uwindsor.ca/etd/7346


University of Michigan

21. Ma, Wen. Dynamic Memristors: from Devices to Applications.

Degree: PhD, Electrical Engineering, 2018, University of Michigan

 Memristors have been extensively studied as a promising candidate for next generation non-volatile memory technology. More recently, memristors have also become extremely popular in neuromorphic(more)

Subjects/Keywords: Memristor; Neuromorphic computing; RRAM; Electrical Engineering; Engineering

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Ma, W. (2018). Dynamic Memristors: from Devices to Applications. (Doctoral Dissertation). University of Michigan. Retrieved from http://hdl.handle.net/2027.42/144102

Chicago Manual of Style (16th Edition):

Ma, Wen. “Dynamic Memristors: from Devices to Applications.” 2018. Doctoral Dissertation, University of Michigan. Accessed November 18, 2019. http://hdl.handle.net/2027.42/144102.

MLA Handbook (7th Edition):

Ma, Wen. “Dynamic Memristors: from Devices to Applications.” 2018. Web. 18 Nov 2019.

Vancouver:

Ma W. Dynamic Memristors: from Devices to Applications. [Internet] [Doctoral dissertation]. University of Michigan; 2018. [cited 2019 Nov 18]. Available from: http://hdl.handle.net/2027.42/144102.

Council of Science Editors:

Ma W. Dynamic Memristors: from Devices to Applications. [Doctoral Dissertation]. University of Michigan; 2018. Available from: http://hdl.handle.net/2027.42/144102


Edith Cowan University

22. Vanarse, Anup. Interfacing of neuromorphic vision, auditory and olfactory sensors with digital neuromorphic circuits.

Degree: 2016, Edith Cowan University

 The conventional Von Neumann architecture imposes strict constraints on the development of intelligent adaptive systems. The requirements of substantial computing power to process and analyse… (more)

Subjects/Keywords: neuromorphic engineering; neuromorphic sensing; AER interfacing; digital neuromorphics; Computer Engineering; Environmental Monitoring

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APA (6th Edition):

Vanarse, A. (2016). Interfacing of neuromorphic vision, auditory and olfactory sensors with digital neuromorphic circuits. (Thesis). Edith Cowan University. Retrieved from http://ro.ecu.edu.au/theses/1802

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Vanarse, Anup. “Interfacing of neuromorphic vision, auditory and olfactory sensors with digital neuromorphic circuits.” 2016. Thesis, Edith Cowan University. Accessed November 18, 2019. http://ro.ecu.edu.au/theses/1802.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Vanarse, Anup. “Interfacing of neuromorphic vision, auditory and olfactory sensors with digital neuromorphic circuits.” 2016. Web. 18 Nov 2019.

Vancouver:

Vanarse A. Interfacing of neuromorphic vision, auditory and olfactory sensors with digital neuromorphic circuits. [Internet] [Thesis]. Edith Cowan University; 2016. [cited 2019 Nov 18]. Available from: http://ro.ecu.edu.au/theses/1802.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Vanarse A. Interfacing of neuromorphic vision, auditory and olfactory sensors with digital neuromorphic circuits. [Thesis]. Edith Cowan University; 2016. Available from: http://ro.ecu.edu.au/theses/1802

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


University of Manchester

23. Liu, Qian. Deep Spiking Neural Networks.

Degree: 2018, University of Manchester

Neuromorphic Engineering (NE) has led to the development of biologically-inspired computer architectures whose long-term goal is to approach the performance of the human brain in… (more)

Subjects/Keywords: Spiking Neural Networks; Deep Learning; Neuromorphic Engineering; Noisy Softplus; Parametric Activation Function; Spike-based Rate Multiplication; Neuromorphic Engineering Dataset

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Liu, Q. (2018). Deep Spiking Neural Networks. (Doctoral Dissertation). University of Manchester. Retrieved from http://www.manchester.ac.uk/escholar/uk-ac-man-scw:313365

Chicago Manual of Style (16th Edition):

Liu, Qian. “Deep Spiking Neural Networks.” 2018. Doctoral Dissertation, University of Manchester. Accessed November 18, 2019. http://www.manchester.ac.uk/escholar/uk-ac-man-scw:313365.

MLA Handbook (7th Edition):

Liu, Qian. “Deep Spiking Neural Networks.” 2018. Web. 18 Nov 2019.

Vancouver:

Liu Q. Deep Spiking Neural Networks. [Internet] [Doctoral dissertation]. University of Manchester; 2018. [cited 2019 Nov 18]. Available from: http://www.manchester.ac.uk/escholar/uk-ac-man-scw:313365.

Council of Science Editors:

Liu Q. Deep Spiking Neural Networks. [Doctoral Dissertation]. University of Manchester; 2018. Available from: http://www.manchester.ac.uk/escholar/uk-ac-man-scw:313365


University of Manchester

24. Liu, Qian. Deep spiking neural networks.

Degree: PhD, 2018, University of Manchester

Neuromorphic Engineering (NE) has led to the development of biologically-inspired computer architectures whose long-term goal is to approach the performance of the human brain in… (more)

Subjects/Keywords: 004; Neuromorphic Engineering Dataset; Spike-based Rate Multiplication; Noisy Softplus; Parametric Activation Function; Deep Learning; Spiking Neural Networks; Neuromorphic Engineering

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APA (6th Edition):

Liu, Q. (2018). Deep spiking neural networks. (Doctoral Dissertation). University of Manchester. Retrieved from https://www.research.manchester.ac.uk/portal/en/theses/deep-spiking-neural-networks(336e6a37-2a0b-41ff-9ffb-cca897220d6c).html ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.740345

Chicago Manual of Style (16th Edition):

Liu, Qian. “Deep spiking neural networks.” 2018. Doctoral Dissertation, University of Manchester. Accessed November 18, 2019. https://www.research.manchester.ac.uk/portal/en/theses/deep-spiking-neural-networks(336e6a37-2a0b-41ff-9ffb-cca897220d6c).html ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.740345.

MLA Handbook (7th Edition):

Liu, Qian. “Deep spiking neural networks.” 2018. Web. 18 Nov 2019.

Vancouver:

Liu Q. Deep spiking neural networks. [Internet] [Doctoral dissertation]. University of Manchester; 2018. [cited 2019 Nov 18]. Available from: https://www.research.manchester.ac.uk/portal/en/theses/deep-spiking-neural-networks(336e6a37-2a0b-41ff-9ffb-cca897220d6c).html ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.740345.

Council of Science Editors:

Liu Q. Deep spiking neural networks. [Doctoral Dissertation]. University of Manchester; 2018. Available from: https://www.research.manchester.ac.uk/portal/en/theses/deep-spiking-neural-networks(336e6a37-2a0b-41ff-9ffb-cca897220d6c).html ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.740345


Texas A&M University

25. Li, Youjie. Energy Efficient Spiking Neuromorphic Architectures for Pattern Recognition.

Degree: MS, Computer Engineering, 2016, Texas A&M University

 There is a growing concern over reliability, power consumption, and performance of traditional Von Neumann machines, especially when dealing with complex tasks like pattern recognition.… (more)

Subjects/Keywords: Neuromorphic VLSI; spiking neural networks; approximate computing; pattern recognition

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APA (6th Edition):

Li, Y. (2016). Energy Efficient Spiking Neuromorphic Architectures for Pattern Recognition. (Masters Thesis). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/156946

Chicago Manual of Style (16th Edition):

Li, Youjie. “Energy Efficient Spiking Neuromorphic Architectures for Pattern Recognition.” 2016. Masters Thesis, Texas A&M University. Accessed November 18, 2019. http://hdl.handle.net/1969.1/156946.

MLA Handbook (7th Edition):

Li, Youjie. “Energy Efficient Spiking Neuromorphic Architectures for Pattern Recognition.” 2016. Web. 18 Nov 2019.

Vancouver:

Li Y. Energy Efficient Spiking Neuromorphic Architectures for Pattern Recognition. [Internet] [Masters thesis]. Texas A&M University; 2016. [cited 2019 Nov 18]. Available from: http://hdl.handle.net/1969.1/156946.

Council of Science Editors:

Li Y. Energy Efficient Spiking Neuromorphic Architectures for Pattern Recognition. [Masters Thesis]. Texas A&M University; 2016. Available from: http://hdl.handle.net/1969.1/156946


RMIT University

26. Murdoch, B. Energetic deposition of dielectric metal oxide coatings.

Degree: 2016, RMIT University

 This thesis examines the optical and electronic properties of wide-bandgap metal oxides grown using energetic deposition methods. The films have also been incorporated in metal/oxide/metal… (more)

Subjects/Keywords: Fields of Research; dielectric; thin film; hafnium oxide; memristor; neuromorphic

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APA (6th Edition):

Murdoch, B. (2016). Energetic deposition of dielectric metal oxide coatings. (Thesis). RMIT University. Retrieved from http://researchbank.rmit.edu.au/view/rmit:161669

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Murdoch, B. “Energetic deposition of dielectric metal oxide coatings.” 2016. Thesis, RMIT University. Accessed November 18, 2019. http://researchbank.rmit.edu.au/view/rmit:161669.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Murdoch, B. “Energetic deposition of dielectric metal oxide coatings.” 2016. Web. 18 Nov 2019.

Vancouver:

Murdoch B. Energetic deposition of dielectric metal oxide coatings. [Internet] [Thesis]. RMIT University; 2016. [cited 2019 Nov 18]. Available from: http://researchbank.rmit.edu.au/view/rmit:161669.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Murdoch B. Energetic deposition of dielectric metal oxide coatings. [Thesis]. RMIT University; 2016. Available from: http://researchbank.rmit.edu.au/view/rmit:161669

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Georgia Tech

27. Nease, Stephen H. Neural and analog computation on reconfigurable mixed-signal platforms.

Degree: PhD, Electrical and Computer Engineering, 2014, Georgia Tech

 This work addresses neural and analog computation on reconfigurable mixed-signal platforms. Many engineered systems could gain tremendous benefits by emulating neural systems. For example, neural… (more)

Subjects/Keywords: Neuromorphic; Field programmable analog array; Analog signal processing

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APA (6th Edition):

Nease, S. H. (2014). Neural and analog computation on reconfigurable mixed-signal platforms. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/53999

Chicago Manual of Style (16th Edition):

Nease, Stephen H. “Neural and analog computation on reconfigurable mixed-signal platforms.” 2014. Doctoral Dissertation, Georgia Tech. Accessed November 18, 2019. http://hdl.handle.net/1853/53999.

MLA Handbook (7th Edition):

Nease, Stephen H. “Neural and analog computation on reconfigurable mixed-signal platforms.” 2014. Web. 18 Nov 2019.

Vancouver:

Nease SH. Neural and analog computation on reconfigurable mixed-signal platforms. [Internet] [Doctoral dissertation]. Georgia Tech; 2014. [cited 2019 Nov 18]. Available from: http://hdl.handle.net/1853/53999.

Council of Science Editors:

Nease SH. Neural and analog computation on reconfigurable mixed-signal platforms. [Doctoral Dissertation]. Georgia Tech; 2014. Available from: http://hdl.handle.net/1853/53999


University of Dayton

28. Wang, Shu. Optimum Microarchitectures for Neuromorphic Algorithms.

Degree: MS(M.S.), Electrical Engineering, 2011, University of Dayton

 At present there is a strong interest in the research community to develop large scale implementations of neuromorphic algorithms. These systems consume significant amounts of… (more)

Subjects/Keywords: Electrical Engineering; neuromorphic; HMAX; Izhikevich; single core; multicore

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APA (6th Edition):

Wang, S. (2011). Optimum Microarchitectures for Neuromorphic Algorithms. (Masters Thesis). University of Dayton. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=dayton1323706763

Chicago Manual of Style (16th Edition):

Wang, Shu. “Optimum Microarchitectures for Neuromorphic Algorithms.” 2011. Masters Thesis, University of Dayton. Accessed November 18, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=dayton1323706763.

MLA Handbook (7th Edition):

Wang, Shu. “Optimum Microarchitectures for Neuromorphic Algorithms.” 2011. Web. 18 Nov 2019.

Vancouver:

Wang S. Optimum Microarchitectures for Neuromorphic Algorithms. [Internet] [Masters thesis]. University of Dayton; 2011. [cited 2019 Nov 18]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=dayton1323706763.

Council of Science Editors:

Wang S. Optimum Microarchitectures for Neuromorphic Algorithms. [Masters Thesis]. University of Dayton; 2011. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=dayton1323706763


University of Dayton

29. Chen, Hua. FPGA Based Multi-core Architectures for Deep Learning Networks.

Degree: MS(M.S.), Electrical Engineering, 2015, University of Dayton

 Deep learning a large scalable network architecture based on neural network. It is currently an extremely active research area in machine learning and pattern recognition… (more)

Subjects/Keywords: Electrical Engineering; Deep learning network; FPGA; neuromorphic processor; Wormhole router

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APA (6th Edition):

Chen, H. (2015). FPGA Based Multi-core Architectures for Deep Learning Networks. (Masters Thesis). University of Dayton. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=dayton1449417091

Chicago Manual of Style (16th Edition):

Chen, Hua. “FPGA Based Multi-core Architectures for Deep Learning Networks.” 2015. Masters Thesis, University of Dayton. Accessed November 18, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=dayton1449417091.

MLA Handbook (7th Edition):

Chen, Hua. “FPGA Based Multi-core Architectures for Deep Learning Networks.” 2015. Web. 18 Nov 2019.

Vancouver:

Chen H. FPGA Based Multi-core Architectures for Deep Learning Networks. [Internet] [Masters thesis]. University of Dayton; 2015. [cited 2019 Nov 18]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=dayton1449417091.

Council of Science Editors:

Chen H. FPGA Based Multi-core Architectures for Deep Learning Networks. [Masters Thesis]. University of Dayton; 2015. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=dayton1449417091


University of Manchester

30. Rast, Alexander Douglas. Scalable event-driven modelling architectures for neuromimetic hardware.

Degree: PhD, 2011, University of Manchester

 Neural networks present a fundamentally different model of computation from the conventional sequential digital model. Dedicated hardware may thus be more suitable for executing them.… (more)

Subjects/Keywords: 004; Event-Driven; Neural; Hardware; Neuromimetic; Neuromorphic; Cognitive

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APA (6th Edition):

Rast, A. D. (2011). Scalable event-driven modelling architectures for neuromimetic hardware. (Doctoral Dissertation). University of Manchester. Retrieved from https://www.research.manchester.ac.uk/portal/en/theses/scalable-eventdriven-modelling-architectures-for-neuromimetic-hardware(0c7f08e1-ad35-4cec-94a5-b765e25bab97).html ; http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.529221

Chicago Manual of Style (16th Edition):

Rast, Alexander Douglas. “Scalable event-driven modelling architectures for neuromimetic hardware.” 2011. Doctoral Dissertation, University of Manchester. Accessed November 18, 2019. https://www.research.manchester.ac.uk/portal/en/theses/scalable-eventdriven-modelling-architectures-for-neuromimetic-hardware(0c7f08e1-ad35-4cec-94a5-b765e25bab97).html ; http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.529221.

MLA Handbook (7th Edition):

Rast, Alexander Douglas. “Scalable event-driven modelling architectures for neuromimetic hardware.” 2011. Web. 18 Nov 2019.

Vancouver:

Rast AD. Scalable event-driven modelling architectures for neuromimetic hardware. [Internet] [Doctoral dissertation]. University of Manchester; 2011. [cited 2019 Nov 18]. Available from: https://www.research.manchester.ac.uk/portal/en/theses/scalable-eventdriven-modelling-architectures-for-neuromimetic-hardware(0c7f08e1-ad35-4cec-94a5-b765e25bab97).html ; http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.529221.

Council of Science Editors:

Rast AD. Scalable event-driven modelling architectures for neuromimetic hardware. [Doctoral Dissertation]. University of Manchester; 2011. Available from: https://www.research.manchester.ac.uk/portal/en/theses/scalable-eventdriven-modelling-architectures-for-neuromimetic-hardware(0c7f08e1-ad35-4cec-94a5-b765e25bab97).html ; http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.529221

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