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You searched for +publisher:"Georgia Tech" +contributor:("Minch, Bradley"). Showing records 1 – 8 of 8 total matches.

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Georgia Tech

1. 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 October 23, 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. 23 Oct 2019.

Vancouver:

Nease SH. Neural and analog computation on reconfigurable mixed-signal platforms. [Internet] [Doctoral dissertation]. Georgia Tech; 2014. [cited 2019 Oct 23]. 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


Georgia Tech

2. Shah, Sahil Sandeep. Low-power computation using FPAA for wearable devices.

Degree: PhD, Electrical and Computer Engineering, 2018, Georgia Tech

 This work investigates low-power mixed-signal computation techniques for real-time applications. The need for real-time processing, with rise of wearable devices, creates a strong drive for… (more)

Subjects/Keywords: Low-power computation; FPAA; Wearable devices

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APA (6th Edition):

Shah, S. S. (2018). Low-power computation using FPAA for wearable devices. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/59918

Chicago Manual of Style (16th Edition):

Shah, Sahil Sandeep. “Low-power computation using FPAA for wearable devices.” 2018. Doctoral Dissertation, Georgia Tech. Accessed October 23, 2019. http://hdl.handle.net/1853/59918.

MLA Handbook (7th Edition):

Shah, Sahil Sandeep. “Low-power computation using FPAA for wearable devices.” 2018. Web. 23 Oct 2019.

Vancouver:

Shah SS. Low-power computation using FPAA for wearable devices. [Internet] [Doctoral dissertation]. Georgia Tech; 2018. [cited 2019 Oct 23]. Available from: http://hdl.handle.net/1853/59918.

Council of Science Editors:

Shah SS. Low-power computation using FPAA for wearable devices. [Doctoral Dissertation]. Georgia Tech; 2018. Available from: http://hdl.handle.net/1853/59918

3. Abramson, David. A mite based translinear fpaa and its practical implementation.

Degree: PhD, Electrical and Computer Engineering, 2008, Georgia Tech

 While the development of reconfigurable analog platforms is a blossoming field, the tradeoff between usability and flexibility continues to be a major barrier. Field Programmable… (more)

Subjects/Keywords: Reconfigurable analog; FPAA; Multiple input translinear elements; Field programmable analog array; Field programmable gate arrays; Analog electronic systems; Signal processing

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APA (6th Edition):

Abramson, D. (2008). A mite based translinear fpaa and its practical implementation. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/26494

Chicago Manual of Style (16th Edition):

Abramson, David. “A mite based translinear fpaa and its practical implementation.” 2008. Doctoral Dissertation, Georgia Tech. Accessed October 23, 2019. http://hdl.handle.net/1853/26494.

MLA Handbook (7th Edition):

Abramson, David. “A mite based translinear fpaa and its practical implementation.” 2008. Web. 23 Oct 2019.

Vancouver:

Abramson D. A mite based translinear fpaa and its practical implementation. [Internet] [Doctoral dissertation]. Georgia Tech; 2008. [cited 2019 Oct 23]. Available from: http://hdl.handle.net/1853/26494.

Council of Science Editors:

Abramson D. A mite based translinear fpaa and its practical implementation. [Doctoral Dissertation]. Georgia Tech; 2008. Available from: http://hdl.handle.net/1853/26494

4. Chiu, Leung Kin. Efficient audio signal processing for embedded systems.

Degree: PhD, Electrical and Computer Engineering, 2012, Georgia Tech

 We investigated two design strategies that would allow us to efficiently process audio signals on embedded systems such as mobile phones and portable electronics. In… (more)

Subjects/Keywords: AdaBoost; Programmable analog circuit; Audio feature selection; Analog classifier; Loudspeaker protection; Sound enhancement; Embedded computer systems; Signal processing Digital techniques; Mobile communication systems; Computer sound processing; Piezoelectric devices; Algorithms

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APA (6th Edition):

Chiu, L. K. (2012). Efficient audio signal processing for embedded systems. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/44775

Chicago Manual of Style (16th Edition):

Chiu, Leung Kin. “Efficient audio signal processing for embedded systems.” 2012. Doctoral Dissertation, Georgia Tech. Accessed October 23, 2019. http://hdl.handle.net/1853/44775.

MLA Handbook (7th Edition):

Chiu, Leung Kin. “Efficient audio signal processing for embedded systems.” 2012. Web. 23 Oct 2019.

Vancouver:

Chiu LK. Efficient audio signal processing for embedded systems. [Internet] [Doctoral dissertation]. Georgia Tech; 2012. [cited 2019 Oct 23]. Available from: http://hdl.handle.net/1853/44775.

Council of Science Editors:

Chiu LK. Efficient audio signal processing for embedded systems. [Doctoral Dissertation]. Georgia Tech; 2012. Available from: http://hdl.handle.net/1853/44775


Georgia Tech

5. Subramanian, Shyam. Methods for synthesis of multiple-input translinear element networks.

Degree: PhD, Electrical and Computer Engineering, 2007, Georgia Tech

 Translinear circuits are circuits in which the exponential relationship between the output current and input voltage of a circuit element is exploited to realize various… (more)

Subjects/Keywords: Translinear loops; Analog circuit synthesis; Log-domain circuits; MITE circuits; Multiple-input translinear element networks; Translinear circuits; Linear integrated circuits; Field programmable gate arrays; Electric filters

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APA (6th Edition):

Subramanian, S. (2007). Methods for synthesis of multiple-input translinear element networks. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/22591

Chicago Manual of Style (16th Edition):

Subramanian, Shyam. “Methods for synthesis of multiple-input translinear element networks.” 2007. Doctoral Dissertation, Georgia Tech. Accessed October 23, 2019. http://hdl.handle.net/1853/22591.

MLA Handbook (7th Edition):

Subramanian, Shyam. “Methods for synthesis of multiple-input translinear element networks.” 2007. Web. 23 Oct 2019.

Vancouver:

Subramanian S. Methods for synthesis of multiple-input translinear element networks. [Internet] [Doctoral dissertation]. Georgia Tech; 2007. [cited 2019 Oct 23]. Available from: http://hdl.handle.net/1853/22591.

Council of Science Editors:

Subramanian S. Methods for synthesis of multiple-input translinear element networks. [Doctoral Dissertation]. Georgia Tech; 2007. Available from: http://hdl.handle.net/1853/22591


Georgia Tech

6. Peng, Sheng-Yu. Charge-based analog circuits for reconfigurable smart sensory systems.

Degree: PhD, Electrical and Computer Engineering, 2008, Georgia Tech

 The notion of designing circuits based on charge sensing, charge adaptation, and charge programming is explored in this research. This design concept leads to a… (more)

Subjects/Keywords: Floating-gate; Analog support vector machine; RBF-classifiers; Capacitive sensing; Analog classifiers; Electronic analog computers Circuits; Microelectronics; Charge coupled devices; Field programmable gate arrays

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APA (6th Edition):

Peng, S. (2008). Charge-based analog circuits for reconfigurable smart sensory systems. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/29655

Chicago Manual of Style (16th Edition):

Peng, Sheng-Yu. “Charge-based analog circuits for reconfigurable smart sensory systems.” 2008. Doctoral Dissertation, Georgia Tech. Accessed October 23, 2019. http://hdl.handle.net/1853/29655.

MLA Handbook (7th Edition):

Peng, Sheng-Yu. “Charge-based analog circuits for reconfigurable smart sensory systems.” 2008. Web. 23 Oct 2019.

Vancouver:

Peng S. Charge-based analog circuits for reconfigurable smart sensory systems. [Internet] [Doctoral dissertation]. Georgia Tech; 2008. [cited 2019 Oct 23]. Available from: http://hdl.handle.net/1853/29655.

Council of Science Editors:

Peng S. Charge-based analog circuits for reconfigurable smart sensory systems. [Doctoral Dissertation]. Georgia Tech; 2008. Available from: http://hdl.handle.net/1853/29655


Georgia Tech

7. Odame, Kofi. Exploiting device nonlinearity in analog circuit design.

Degree: PhD, Electrical and Computer Engineering, 2008, Georgia Tech

 This dissertation presents analog circuit analysis and design from a nonlinear dynamics perspective. An introduction to fundamental concepts of nonlinear dynamical systems theory is given.… (more)

Subjects/Keywords: Silicon cochlea; Nonlinear oscillators; Nonlinear dynamics; Analog integrated circuits; Electronic analog computers Circuits Design; Nonlinear theories; Dynamics

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APA (6th Edition):

Odame, K. (2008). Exploiting device nonlinearity in analog circuit design. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/29751

Chicago Manual of Style (16th Edition):

Odame, Kofi. “Exploiting device nonlinearity in analog circuit design.” 2008. Doctoral Dissertation, Georgia Tech. Accessed October 23, 2019. http://hdl.handle.net/1853/29751.

MLA Handbook (7th Edition):

Odame, Kofi. “Exploiting device nonlinearity in analog circuit design.” 2008. Web. 23 Oct 2019.

Vancouver:

Odame K. Exploiting device nonlinearity in analog circuit design. [Internet] [Doctoral dissertation]. Georgia Tech; 2008. [cited 2019 Oct 23]. Available from: http://hdl.handle.net/1853/29751.

Council of Science Editors:

Odame K. Exploiting device nonlinearity in analog circuit design. [Doctoral Dissertation]. Georgia Tech; 2008. Available from: http://hdl.handle.net/1853/29751


Georgia Tech

8. Smith, Paul Devon. An Analog Architecture for Auditory Feature Extraction and Recognition.

Degree: PhD, Electrical and Computer Engineering, 2004, Georgia Tech

 Speech recognition systems have been implemented using a wide range of signal processing techniques including neuromorphic/biological inspired and Digital Signal Processing techniques. Neuromorphic/biologically inspired techniques,… (more)

Subjects/Keywords: Neuromorphic cochlea; Hidden Markov Model (HMM); Cepstrum; Speech processing systems; Signal processing Digital techniques; Speech processing systems; Cochlea Models; Markov processes; Neural networks (Computer science)

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APA (6th Edition):

Smith, P. D. (2004). An Analog Architecture for Auditory Feature Extraction and Recognition. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/4839

Chicago Manual of Style (16th Edition):

Smith, Paul Devon. “An Analog Architecture for Auditory Feature Extraction and Recognition.” 2004. Doctoral Dissertation, Georgia Tech. Accessed October 23, 2019. http://hdl.handle.net/1853/4839.

MLA Handbook (7th Edition):

Smith, Paul Devon. “An Analog Architecture for Auditory Feature Extraction and Recognition.” 2004. Web. 23 Oct 2019.

Vancouver:

Smith PD. An Analog Architecture for Auditory Feature Extraction and Recognition. [Internet] [Doctoral dissertation]. Georgia Tech; 2004. [cited 2019 Oct 23]. Available from: http://hdl.handle.net/1853/4839.

Council of Science Editors:

Smith PD. An Analog Architecture for Auditory Feature Extraction and Recognition. [Doctoral Dissertation]. Georgia Tech; 2004. Available from: http://hdl.handle.net/1853/4839

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