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You searched for subject:(neuromorphic architecture). Showing records 1 – 12 of 12 total matches.

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University of Cincinnati

1. Morabito, Giovanni V. Architecture and Neuroscience: Designing for How the Brain Responds to the Built Environment.

Degree: M. Arch., Design, Architecture, Art and Planning: Architecture, 2016, University of Cincinnati

 Architects have long been uncertain about how the spacesand buildings they design affect the people who inhabit theseenvironments on a neurological level. Regardless of this,… (more)

Subjects/Keywords: Architecture; Architecture and Neuroscience; Environmental Cognition; Neuroplasticity; Neuroscience and Design; Mind Mapping; Neuromorphic Architecture

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APA (6th Edition):

Morabito, G. V. (2016). Architecture and Neuroscience: Designing for How the Brain Responds to the Built Environment. (Masters Thesis). University of Cincinnati. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=ucin1460729866

Chicago Manual of Style (16th Edition):

Morabito, Giovanni V. “Architecture and Neuroscience: Designing for How the Brain Responds to the Built Environment.” 2016. Masters Thesis, University of Cincinnati. Accessed August 22, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1460729866.

MLA Handbook (7th Edition):

Morabito, Giovanni V. “Architecture and Neuroscience: Designing for How the Brain Responds to the Built Environment.” 2016. Web. 22 Aug 2019.

Vancouver:

Morabito GV. Architecture and Neuroscience: Designing for How the Brain Responds to the Built Environment. [Internet] [Masters thesis]. University of Cincinnati; 2016. [cited 2019 Aug 22]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=ucin1460729866.

Council of Science Editors:

Morabito GV. Architecture and Neuroscience: Designing for How the Brain Responds to the Built Environment. [Masters Thesis]. University of Cincinnati; 2016. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=ucin1460729866


University of Tennessee – Knoxville

2. Mitchell, John Parker. DANNA2: Dynamic Adaptive Neural Network Arrays.

Degree: MS, Computer Engineering, 2018, University of Tennessee – Knoxville

 Traditional Von Neumann architectures have been at the center of computing for decades thanks in part to Moore's Law and Dennard Scaling. However, MOSFET scaling… (more)

Subjects/Keywords: neuromorphic; spiking neural networks; computer architecture; machine learning

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APA (6th Edition):

Mitchell, J. P. (2018). DANNA2: Dynamic Adaptive Neural Network Arrays. (Thesis). University of Tennessee – Knoxville. Retrieved from https://trace.tennessee.edu/utk_gradthes/5167

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):

Mitchell, John Parker. “DANNA2: Dynamic Adaptive Neural Network Arrays.” 2018. Thesis, University of Tennessee – Knoxville. Accessed August 22, 2019. https://trace.tennessee.edu/utk_gradthes/5167.

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

MLA Handbook (7th Edition):

Mitchell, John Parker. “DANNA2: Dynamic Adaptive Neural Network Arrays.” 2018. Web. 22 Aug 2019.

Vancouver:

Mitchell JP. DANNA2: Dynamic Adaptive Neural Network Arrays. [Internet] [Thesis]. University of Tennessee – Knoxville; 2018. [cited 2019 Aug 22]. Available from: https://trace.tennessee.edu/utk_gradthes/5167.

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

Council of Science Editors:

Mitchell JP. DANNA2: Dynamic Adaptive Neural Network Arrays. [Thesis]. University of Tennessee – Knoxville; 2018. Available from: https://trace.tennessee.edu/utk_gradthes/5167

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


University of Tennessee – Knoxville

3. Eckhart, Patricia Jean. Tiled DANNA: Dynamic Adaptive Neural Network Array Scaled Across Multiple Chips.

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

  Tiled Dynamic Adaptive Neural Network Array(Tiled DANNA) is a recurrent spiking neural network structure composed of programmable biologically inspired neurons and synapses that scales… (more)

Subjects/Keywords: neuromorphic; FPGA; spiking neural network; interconnect; Computer and Systems Architecture

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APA (6th Edition):

Eckhart, P. J. (2017). Tiled DANNA: Dynamic Adaptive Neural Network Array Scaled Across Multiple Chips. (Thesis). University of Tennessee – Knoxville. Retrieved from https://trace.tennessee.edu/utk_gradthes/4870

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):

Eckhart, Patricia Jean. “Tiled DANNA: Dynamic Adaptive Neural Network Array Scaled Across Multiple Chips.” 2017. Thesis, University of Tennessee – Knoxville. Accessed August 22, 2019. https://trace.tennessee.edu/utk_gradthes/4870.

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

MLA Handbook (7th Edition):

Eckhart, Patricia Jean. “Tiled DANNA: Dynamic Adaptive Neural Network Array Scaled Across Multiple Chips.” 2017. Web. 22 Aug 2019.

Vancouver:

Eckhart PJ. Tiled DANNA: Dynamic Adaptive Neural Network Array Scaled Across Multiple Chips. [Internet] [Thesis]. University of Tennessee – Knoxville; 2017. [cited 2019 Aug 22]. Available from: https://trace.tennessee.edu/utk_gradthes/4870.

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

Council of Science Editors:

Eckhart PJ. Tiled DANNA: Dynamic Adaptive Neural Network Array Scaled Across Multiple Chips. [Thesis]. University of Tennessee – Knoxville; 2017. Available from: https://trace.tennessee.edu/utk_gradthes/4870

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


University of Tennessee – Knoxville

4. Young, Aaron Reed. Scalable High-Speed Communications for Neuromorphic Systems.

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

  Field-programmable gate arrays (FPGA), application-specific integrated circuits (ASIC), and other chip/multi-chip level implementations can be used to implement Dynamic Adaptive Neural Network Arrays (DANNA).… (more)

Subjects/Keywords: Neuromorphic; Computer Architecture; Communication; High-Speed; Aurora; FPGA; Computer and Systems Architecture; Computer Engineering; Digital Communications and Networking; Hardware Systems

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APA (6th Edition):

Young, A. R. (2017). Scalable High-Speed Communications for Neuromorphic Systems. (Thesis). University of Tennessee – Knoxville. Retrieved from https://trace.tennessee.edu/utk_gradthes/4916

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):

Young, Aaron Reed. “Scalable High-Speed Communications for Neuromorphic Systems.” 2017. Thesis, University of Tennessee – Knoxville. Accessed August 22, 2019. https://trace.tennessee.edu/utk_gradthes/4916.

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

MLA Handbook (7th Edition):

Young, Aaron Reed. “Scalable High-Speed Communications for Neuromorphic Systems.” 2017. Web. 22 Aug 2019.

Vancouver:

Young AR. Scalable High-Speed Communications for Neuromorphic Systems. [Internet] [Thesis]. University of Tennessee – Knoxville; 2017. [cited 2019 Aug 22]. Available from: https://trace.tennessee.edu/utk_gradthes/4916.

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

Council of Science Editors:

Young AR. Scalable High-Speed Communications for Neuromorphic Systems. [Thesis]. University of Tennessee – Knoxville; 2017. Available from: https://trace.tennessee.edu/utk_gradthes/4916

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


University of Michigan

5. Zheng, Nan. Algorithm/Architecture Co-Design for Low-Power Neuromorphic Computing.

Degree: PhD, Electrical Engineering, 2017, University of Michigan

 The development of computing systems based on the conventional von Neumann architecture has slowed down in the past decade as complementary metal-oxide-semiconductor (CMOS) technology scaling… (more)

Subjects/Keywords: Neuromorphic computing; Neural network; Machine learning; Low-power circuit; Hardware architecture; Algorithm-architecture co-design; Computer Science; Electrical Engineering; Engineering; Science

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APA (6th Edition):

Zheng, N. (2017). Algorithm/Architecture Co-Design for Low-Power Neuromorphic Computing. (Doctoral Dissertation). University of Michigan. Retrieved from http://hdl.handle.net/2027.42/144149

Chicago Manual of Style (16th Edition):

Zheng, Nan. “Algorithm/Architecture Co-Design for Low-Power Neuromorphic Computing.” 2017. Doctoral Dissertation, University of Michigan. Accessed August 22, 2019. http://hdl.handle.net/2027.42/144149.

MLA Handbook (7th Edition):

Zheng, Nan. “Algorithm/Architecture Co-Design for Low-Power Neuromorphic Computing.” 2017. Web. 22 Aug 2019.

Vancouver:

Zheng N. Algorithm/Architecture Co-Design for Low-Power Neuromorphic Computing. [Internet] [Doctoral dissertation]. University of Michigan; 2017. [cited 2019 Aug 22]. Available from: http://hdl.handle.net/2027.42/144149.

Council of Science Editors:

Zheng N. Algorithm/Architecture Co-Design for Low-Power Neuromorphic Computing. [Doctoral Dissertation]. University of Michigan; 2017. Available from: http://hdl.handle.net/2027.42/144149


Boise State University

6. Wu, Xinyu. Analog Spiking Neuromorphic Circuits and Systems for Brain- and Nanotechnology-Inspired Cognitive Computing.

Degree: 2016, Boise State University

 Human society is now facing grand challenges to satisfy the growing demand for computing power, at the same time, sustain energy consumption. By the end… (more)

Subjects/Keywords: neuromorphic; spiking neural network; VLSI; emerging memory device; machine learning; pattern recongnition; Bioelectrical and Neuroengineering; Computer and Systems Architecture; Nanoscience and Nanotechnology; VLSI and Circuits, Embedded and Hardware Systems

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APA (6th Edition):

Wu, X. (2016). Analog Spiking Neuromorphic Circuits and Systems for Brain- and Nanotechnology-Inspired Cognitive Computing. (Thesis). Boise State University. Retrieved from https://scholarworks.boisestate.edu/td/1239

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):

Wu, Xinyu. “Analog Spiking Neuromorphic Circuits and Systems for Brain- and Nanotechnology-Inspired Cognitive Computing.” 2016. Thesis, Boise State University. Accessed August 22, 2019. https://scholarworks.boisestate.edu/td/1239.

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

MLA Handbook (7th Edition):

Wu, Xinyu. “Analog Spiking Neuromorphic Circuits and Systems for Brain- and Nanotechnology-Inspired Cognitive Computing.” 2016. Web. 22 Aug 2019.

Vancouver:

Wu X. Analog Spiking Neuromorphic Circuits and Systems for Brain- and Nanotechnology-Inspired Cognitive Computing. [Internet] [Thesis]. Boise State University; 2016. [cited 2019 Aug 22]. Available from: https://scholarworks.boisestate.edu/td/1239.

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

Council of Science Editors:

Wu X. Analog Spiking Neuromorphic Circuits and Systems for Brain- and Nanotechnology-Inspired Cognitive Computing. [Thesis]. Boise State University; 2016. Available from: https://scholarworks.boisestate.edu/td/1239

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

7. Willis, Joshua Caleb. Middleware and Services for Dynamic Adaptive Neural Network Arrays.

Degree: MS, Computer Science, 2015, University of Tennessee – Knoxville

  Dynamic Adaptive Neural Network Arrays (DANNAs) are neuromorphic systems that exhibit spiking behaviors and can be designed using evolutionary optimization. Array elements are rapidly… (more)

Subjects/Keywords: neuromorphic computing; middleware; software engineering; Computer and Systems Architecture

…computing group, including Neuromorphic-Inspired Dynamic Architecture (NIDA) and DANNA… …2.1.1 Background Neuromorphic-Inspired Dynamic Architecture A Neuromorphic-Inspired Dynamic… …Architecture The Neuromorphic Instruction Set Architecture (NISA) [23]… …Neural Network Arrays (DANNAs) [42] [1] are neuromorphic systems… …changes in the design of DANNA, including changes to the DANNA architecture, DANNA 1… 

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APA (6th Edition):

Willis, J. C. (2015). Middleware and Services for Dynamic Adaptive Neural Network Arrays. (Thesis). University of Tennessee – Knoxville. Retrieved from https://trace.tennessee.edu/utk_gradthes/3527

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):

Willis, Joshua Caleb. “Middleware and Services for Dynamic Adaptive Neural Network Arrays.” 2015. Thesis, University of Tennessee – Knoxville. Accessed August 22, 2019. https://trace.tennessee.edu/utk_gradthes/3527.

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

MLA Handbook (7th Edition):

Willis, Joshua Caleb. “Middleware and Services for Dynamic Adaptive Neural Network Arrays.” 2015. Web. 22 Aug 2019.

Vancouver:

Willis JC. Middleware and Services for Dynamic Adaptive Neural Network Arrays. [Internet] [Thesis]. University of Tennessee – Knoxville; 2015. [cited 2019 Aug 22]. Available from: https://trace.tennessee.edu/utk_gradthes/3527.

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

Council of Science Editors:

Willis JC. Middleware and Services for Dynamic Adaptive Neural Network Arrays. [Thesis]. University of Tennessee – Knoxville; 2015. Available from: https://trace.tennessee.edu/utk_gradthes/3527

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


University of Canterbury

8. Brown SA. Stable Self-Assembled Atomic-Switch Networks for Neuromorphic Applications.

Degree: 2017, University of Canterbury

 IEEE Nature-inspired neuromorphic architectures are being explored as an alternative to imminent limitations of conventional complementary metal-oxide semiconductor architectures. Utilization of such architectures for practical… (more)

Subjects/Keywords: Atomic-switch networks (ASNs); clusters; neuromorphic architecture; Field of Research::10 - Technology::1007 - Nanotechnology::100703 - Nanobiotechnology; Field of Research::10 - Technology::1007 - Nanotechnology::100702 - Molecular and Organic Electronics

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APA (6th Edition):

SA, B. (2017). Stable Self-Assembled Atomic-Switch Networks for Neuromorphic Applications. (Thesis). University of Canterbury. Retrieved from http://hdl.handle.net/10092/16324

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):

SA, Brown. “Stable Self-Assembled Atomic-Switch Networks for Neuromorphic Applications.” 2017. Thesis, University of Canterbury. Accessed August 22, 2019. http://hdl.handle.net/10092/16324.

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

MLA Handbook (7th Edition):

SA, Brown. “Stable Self-Assembled Atomic-Switch Networks for Neuromorphic Applications.” 2017. Web. 22 Aug 2019.

Vancouver:

SA B. Stable Self-Assembled Atomic-Switch Networks for Neuromorphic Applications. [Internet] [Thesis]. University of Canterbury; 2017. [cited 2019 Aug 22]. Available from: http://hdl.handle.net/10092/16324.

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

Council of Science Editors:

SA B. Stable Self-Assembled Atomic-Switch Networks for Neuromorphic Applications. [Thesis]. University of Canterbury; 2017. Available from: http://hdl.handle.net/10092/16324

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


University of Tennessee – Knoxville

9. Chan, Jason Yen-Shen. Implementation of a Neuromorphic Development Platform with DANNA.

Degree: MS, Electrical Engineering, 2015, University of Tennessee – Knoxville

Neuromorphic computing is the use of artificial neural networks to solve complex problems. The specialized computing field has been growing in interest during the… (more)

Subjects/Keywords: Neural Networks; Neuromorphic Computing; Neuroscience-Inspired Architectures; Development Platform; Computer and Systems Architecture; Computer Engineering; Electrical and Computer Engineering; Electrical and Electronics; Hardware Systems

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APA (6th Edition):

Chan, J. Y. (2015). Implementation of a Neuromorphic Development Platform with DANNA. (Thesis). University of Tennessee – Knoxville. Retrieved from https://trace.tennessee.edu/utk_gradthes/3569

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):

Chan, Jason Yen-Shen. “Implementation of a Neuromorphic Development Platform with DANNA.” 2015. Thesis, University of Tennessee – Knoxville. Accessed August 22, 2019. https://trace.tennessee.edu/utk_gradthes/3569.

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

MLA Handbook (7th Edition):

Chan, Jason Yen-Shen. “Implementation of a Neuromorphic Development Platform with DANNA.” 2015. Web. 22 Aug 2019.

Vancouver:

Chan JY. Implementation of a Neuromorphic Development Platform with DANNA. [Internet] [Thesis]. University of Tennessee – Knoxville; 2015. [cited 2019 Aug 22]. Available from: https://trace.tennessee.edu/utk_gradthes/3569.

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

Council of Science Editors:

Chan JY. Implementation of a Neuromorphic Development Platform with DANNA. [Thesis]. University of Tennessee – Knoxville; 2015. Available from: https://trace.tennessee.edu/utk_gradthes/3569

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


Université Paris-Sud – Paris XI

10. Roclin, David. Utilisation des nano-composants électroniques dans les architectures de traitement associées aux imageurs : Integration of memory nano-devices in image sensors processing architecture.

Degree: Docteur es, Physique, 2014, Université Paris-Sud – Paris XI

En utilisant les méthodes d’apprentissages tirées des récentes découvertes en neuroscience, les réseaux de neurones impulsionnels ont démontrés leurs capacités à analyser efficacement les grandes… (more)

Subjects/Keywords: Memristor; Dispositif memristif; Réseau de neurones impulsionnels; Système neuromorphique; Spike-timing-dependent plasticity; Memristor; Memristive device; Spiking Neural Networks; Neuromorphic architecture; Spike-timing-dependent plasticity

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APA (6th Edition):

Roclin, D. (2014). Utilisation des nano-composants électroniques dans les architectures de traitement associées aux imageurs : Integration of memory nano-devices in image sensors processing architecture. (Doctoral Dissertation). Université Paris-Sud – Paris XI. Retrieved from http://www.theses.fr/2014PA112408

Chicago Manual of Style (16th Edition):

Roclin, David. “Utilisation des nano-composants électroniques dans les architectures de traitement associées aux imageurs : Integration of memory nano-devices in image sensors processing architecture.” 2014. Doctoral Dissertation, Université Paris-Sud – Paris XI. Accessed August 22, 2019. http://www.theses.fr/2014PA112408.

MLA Handbook (7th Edition):

Roclin, David. “Utilisation des nano-composants électroniques dans les architectures de traitement associées aux imageurs : Integration of memory nano-devices in image sensors processing architecture.” 2014. Web. 22 Aug 2019.

Vancouver:

Roclin D. Utilisation des nano-composants électroniques dans les architectures de traitement associées aux imageurs : Integration of memory nano-devices in image sensors processing architecture. [Internet] [Doctoral dissertation]. Université Paris-Sud – Paris XI; 2014. [cited 2019 Aug 22]. Available from: http://www.theses.fr/2014PA112408.

Council of Science Editors:

Roclin D. Utilisation des nano-composants électroniques dans les architectures de traitement associées aux imageurs : Integration of memory nano-devices in image sensors processing architecture. [Doctoral Dissertation]. Université Paris-Sud – Paris XI; 2014. Available from: http://www.theses.fr/2014PA112408

11. Hasan, Md. Raqibul. Multi-core Architectures for Feed-forward Neural Networks.

Degree: MS(M.S.), Electrical Engineering, 2014, University of Dayton

 Power density constraints and processor reliability concerns are causing energy efficient processor architectures to gain more interest in recent years. One approach to reduce processor… (more)

Subjects/Keywords: Electrical Engineering; Multi-core architectures, neuromorphic architecture, on-chip routing, memristor crossbar, specialized core

…performance at extreme low power, specialized multi-core neuromorphic architecture could be a viable… …28 4.2 Static Routing and Application to Neuromorphic Architectures ….29 4.3… …architecture . 37 21. Proposed multi-core system with several neural cores (NC… …multi-core neuromorphic architectures processing large multi-layered feed forward neural… …networks. 1.1 Processor Architecture Trend Reliability and power consumption are among the main… 

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APA (6th Edition):

Hasan, M. R. (2014). Multi-core Architectures for Feed-forward Neural Networks. (Masters Thesis). University of Dayton. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=dayton1395140542

Chicago Manual of Style (16th Edition):

Hasan, Md Raqibul. “Multi-core Architectures for Feed-forward Neural Networks.” 2014. Masters Thesis, University of Dayton. Accessed August 22, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=dayton1395140542.

MLA Handbook (7th Edition):

Hasan, Md Raqibul. “Multi-core Architectures for Feed-forward Neural Networks.” 2014. Web. 22 Aug 2019.

Vancouver:

Hasan MR. Multi-core Architectures for Feed-forward Neural Networks. [Internet] [Masters thesis]. University of Dayton; 2014. [cited 2019 Aug 22]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=dayton1395140542.

Council of Science Editors:

Hasan MR. Multi-core Architectures for Feed-forward Neural Networks. [Masters Thesis]. University of Dayton; 2014. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=dayton1395140542

12. Rodriguez, Laurent. Définition d'un substrat computationnel bio-inspiré : déclinaison de propriétés de plasticité cérébrale dans les architectures de traitement auto-adaptatif : Design of a bio-inspired computing substrata : hardware plasticity properties for self-adaptive computing architectures.

Degree: Docteur es, STIC (sciences et technologies de l'information et de la communication) - Cergy, 2015, Cergy-Pontoise

 L'augmentation du parallélisme, sur des puces dont la densité d'intégration est en constante croissance, soulève un certain nombre de défis tels que le routage de… (more)

Subjects/Keywords: Architectures auto-Adaptatives; Réseaux de neurones artificiels; Cartes auto-Organisatrices; Plasticité matérielle; Calcul neuromorphique; Calcul incorporé; Self-Adaptive architecture; Artificial neural networks; Self Organizing Maps; Hardware plasticity; Neuromorphic computing; Embodied computing

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APA (6th Edition):

Rodriguez, L. (2015). Définition d'un substrat computationnel bio-inspiré : déclinaison de propriétés de plasticité cérébrale dans les architectures de traitement auto-adaptatif : Design of a bio-inspired computing substrata : hardware plasticity properties for self-adaptive computing architectures. (Doctoral Dissertation). Cergy-Pontoise. Retrieved from http://www.theses.fr/2015CERG0765

Chicago Manual of Style (16th Edition):

Rodriguez, Laurent. “Définition d'un substrat computationnel bio-inspiré : déclinaison de propriétés de plasticité cérébrale dans les architectures de traitement auto-adaptatif : Design of a bio-inspired computing substrata : hardware plasticity properties for self-adaptive computing architectures.” 2015. Doctoral Dissertation, Cergy-Pontoise. Accessed August 22, 2019. http://www.theses.fr/2015CERG0765.

MLA Handbook (7th Edition):

Rodriguez, Laurent. “Définition d'un substrat computationnel bio-inspiré : déclinaison de propriétés de plasticité cérébrale dans les architectures de traitement auto-adaptatif : Design of a bio-inspired computing substrata : hardware plasticity properties for self-adaptive computing architectures.” 2015. Web. 22 Aug 2019.

Vancouver:

Rodriguez L. Définition d'un substrat computationnel bio-inspiré : déclinaison de propriétés de plasticité cérébrale dans les architectures de traitement auto-adaptatif : Design of a bio-inspired computing substrata : hardware plasticity properties for self-adaptive computing architectures. [Internet] [Doctoral dissertation]. Cergy-Pontoise; 2015. [cited 2019 Aug 22]. Available from: http://www.theses.fr/2015CERG0765.

Council of Science Editors:

Rodriguez L. Définition d'un substrat computationnel bio-inspiré : déclinaison de propriétés de plasticité cérébrale dans les architectures de traitement auto-adaptatif : Design of a bio-inspired computing substrata : hardware plasticity properties for self-adaptive computing architectures. [Doctoral Dissertation]. Cergy-Pontoise; 2015. Available from: http://www.theses.fr/2015CERG0765

.