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Dates: 2015 – 2019

You searched for subject:(STDP). Showing records 1 – 15 of 15 total matches.

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Texas A&M University

1. Thulasiraman, Kumaran. Enhanced Reinforcement Learning with Attentional Feedback and Temporally Attenuated Distal Rewards.

Degree: 2015, Texas A&M University

 This thesis presents a new reinforcement learning mechanism suitable to be employed in artificial spiking neural networks of leaky integrate-and-fire (LIF) or Izhikevich neurons. The… (more)

Subjects/Keywords: reinforcement learning; spiking neural networks; dopamine-modulated; STDP

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APA (6th Edition):

Thulasiraman, K. (2015). Enhanced Reinforcement Learning with Attentional Feedback and Temporally Attenuated Distal Rewards. (Thesis). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/155519

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):

Thulasiraman, Kumaran. “Enhanced Reinforcement Learning with Attentional Feedback and Temporally Attenuated Distal Rewards.” 2015. Thesis, Texas A&M University. Accessed December 05, 2019. http://hdl.handle.net/1969.1/155519.

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

MLA Handbook (7th Edition):

Thulasiraman, Kumaran. “Enhanced Reinforcement Learning with Attentional Feedback and Temporally Attenuated Distal Rewards.” 2015. Web. 05 Dec 2019.

Vancouver:

Thulasiraman K. Enhanced Reinforcement Learning with Attentional Feedback and Temporally Attenuated Distal Rewards. [Internet] [Thesis]. Texas A&M University; 2015. [cited 2019 Dec 05]. Available from: http://hdl.handle.net/1969.1/155519.

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

Council of Science Editors:

Thulasiraman K. Enhanced Reinforcement Learning with Attentional Feedback and Temporally Attenuated Distal Rewards. [Thesis]. Texas A&M University; 2015. Available from: http://hdl.handle.net/1969.1/155519

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


University of Sydney

2. Palmer, John H.C. Propagating spike waves in neural circuits: formation mechanisms and functional roles .

Degree: 2016, University of Sydney

 Propagating spike waves are a ubiquitous type of activity within the brain. However, both their formation mechanisms and functional roles remain largely unknown. In this… (more)

Subjects/Keywords: spiking neural circuits; plasticity; STDP; associative learning; spike waves

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APA (6th Edition):

Palmer, J. H. C. (2016). Propagating spike waves in neural circuits: formation mechanisms and functional roles . (Thesis). University of Sydney. Retrieved from http://hdl.handle.net/2123/16758

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):

Palmer, John H C. “Propagating spike waves in neural circuits: formation mechanisms and functional roles .” 2016. Thesis, University of Sydney. Accessed December 05, 2019. http://hdl.handle.net/2123/16758.

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

MLA Handbook (7th Edition):

Palmer, John H C. “Propagating spike waves in neural circuits: formation mechanisms and functional roles .” 2016. Web. 05 Dec 2019.

Vancouver:

Palmer JHC. Propagating spike waves in neural circuits: formation mechanisms and functional roles . [Internet] [Thesis]. University of Sydney; 2016. [cited 2019 Dec 05]. Available from: http://hdl.handle.net/2123/16758.

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

Council of Science Editors:

Palmer JHC. Propagating spike waves in neural circuits: formation mechanisms and functional roles . [Thesis]. University of Sydney; 2016. Available from: http://hdl.handle.net/2123/16758

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

3. Drake, Kolton T. Biomimetic Application of Ion-Conducting-Based Memristive Devices in Spike-Timing-Dependent-Plasticity.

Degree: 2015, Boise State University

 The design and synthesis of artificial learning systems has been aided by the study of biological learning systems. Classic biological learning is driven by the… (more)

Subjects/Keywords: memristor; neuromorphic; STDP; biomimetics; Electrical and Computer Engineering

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APA (6th Edition):

Drake, K. T. (2015). Biomimetic Application of Ion-Conducting-Based Memristive Devices in Spike-Timing-Dependent-Plasticity. (Thesis). Boise State University. Retrieved from https://scholarworks.boisestate.edu/td/1001

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):

Drake, Kolton T. “Biomimetic Application of Ion-Conducting-Based Memristive Devices in Spike-Timing-Dependent-Plasticity.” 2015. Thesis, Boise State University. Accessed December 05, 2019. https://scholarworks.boisestate.edu/td/1001.

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

MLA Handbook (7th Edition):

Drake, Kolton T. “Biomimetic Application of Ion-Conducting-Based Memristive Devices in Spike-Timing-Dependent-Plasticity.” 2015. Web. 05 Dec 2019.

Vancouver:

Drake KT. Biomimetic Application of Ion-Conducting-Based Memristive Devices in Spike-Timing-Dependent-Plasticity. [Internet] [Thesis]. Boise State University; 2015. [cited 2019 Dec 05]. Available from: https://scholarworks.boisestate.edu/td/1001.

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

Council of Science Editors:

Drake KT. Biomimetic Application of Ion-Conducting-Based Memristive Devices in Spike-Timing-Dependent-Plasticity. [Thesis]. Boise State University; 2015. Available from: https://scholarworks.boisestate.edu/td/1001

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


University of Toronto

4. Himberger, Kevin D. A Spiking Circuit Model of Sequence Learning.

Degree: 2015, University of Toronto

The ability to integrate information over time is fundamental to cognition. Any sensory experience, from object recognition to speech comprehension, utilizes this ability. Contrary to… (more)

Subjects/Keywords: model; plasticity; process memory; sequence learning; spiking; STDP; 0317

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APA (6th Edition):

Himberger, K. D. (2015). A Spiking Circuit Model of Sequence Learning. (Masters Thesis). University of Toronto. Retrieved from http://hdl.handle.net/1807/70418

Chicago Manual of Style (16th Edition):

Himberger, Kevin D. “A Spiking Circuit Model of Sequence Learning.” 2015. Masters Thesis, University of Toronto. Accessed December 05, 2019. http://hdl.handle.net/1807/70418.

MLA Handbook (7th Edition):

Himberger, Kevin D. “A Spiking Circuit Model of Sequence Learning.” 2015. Web. 05 Dec 2019.

Vancouver:

Himberger KD. A Spiking Circuit Model of Sequence Learning. [Internet] [Masters thesis]. University of Toronto; 2015. [cited 2019 Dec 05]. Available from: http://hdl.handle.net/1807/70418.

Council of Science Editors:

Himberger KD. A Spiking Circuit Model of Sequence Learning. [Masters Thesis]. University of Toronto; 2015. Available from: http://hdl.handle.net/1807/70418


NSYSU

5. Su, Wan-ching. Study on the Bionic Synapse Application of Lithium aluminum oxide Non-Volatile Resistance Random Access Memory.

Degree: Master, Mechanical and Electro-Mechanical Engineering, 2015, NSYSU

 Since long time ago, the nature being has been the source of humanâs senses of invention principles productions, in which bionic technology has been well… (more)

Subjects/Keywords: Neural Networks; Lithium Aluminum Oxide; STDP; Multi-Bits Access; Multi-Filament; RRAM

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APA (6th Edition):

Su, W. (2015). Study on the Bionic Synapse Application of Lithium aluminum oxide Non-Volatile Resistance Random Access Memory. (Thesis). NSYSU. Retrieved from http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0317115-123644

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):

Su, Wan-ching. “Study on the Bionic Synapse Application of Lithium aluminum oxide Non-Volatile Resistance Random Access Memory.” 2015. Thesis, NSYSU. Accessed December 05, 2019. http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0317115-123644.

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

MLA Handbook (7th Edition):

Su, Wan-ching. “Study on the Bionic Synapse Application of Lithium aluminum oxide Non-Volatile Resistance Random Access Memory.” 2015. Web. 05 Dec 2019.

Vancouver:

Su W. Study on the Bionic Synapse Application of Lithium aluminum oxide Non-Volatile Resistance Random Access Memory. [Internet] [Thesis]. NSYSU; 2015. [cited 2019 Dec 05]. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0317115-123644.

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

Council of Science Editors:

Su W. Study on the Bionic Synapse Application of Lithium aluminum oxide Non-Volatile Resistance Random Access Memory. [Thesis]. NSYSU; 2015. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0317115-123644

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


Arizona State University

6. Mahalanabis, Debayan. Multilevel Resistance Programming in Conductive Bridge Resistive Memory.

Degree: Electrical Engineering, 2015, Arizona State University

 This work focuses on the existence of multiple resistance states in a type of emerging non-volatile resistive memory device known commonly as Programmable Metallization Cell… (more)

Subjects/Keywords: Electrical engineering; Nanotechnology; CBRAM; Compact Model; Neuromorphic Computing; Non-volatile Memory; Resistive Memory; STDP

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APA (6th Edition):

Mahalanabis, D. (2015). Multilevel Resistance Programming in Conductive Bridge Resistive Memory. (Doctoral Dissertation). Arizona State University. Retrieved from http://repository.asu.edu/items/36417

Chicago Manual of Style (16th Edition):

Mahalanabis, Debayan. “Multilevel Resistance Programming in Conductive Bridge Resistive Memory.” 2015. Doctoral Dissertation, Arizona State University. Accessed December 05, 2019. http://repository.asu.edu/items/36417.

MLA Handbook (7th Edition):

Mahalanabis, Debayan. “Multilevel Resistance Programming in Conductive Bridge Resistive Memory.” 2015. Web. 05 Dec 2019.

Vancouver:

Mahalanabis D. Multilevel Resistance Programming in Conductive Bridge Resistive Memory. [Internet] [Doctoral dissertation]. Arizona State University; 2015. [cited 2019 Dec 05]. Available from: http://repository.asu.edu/items/36417.

Council of Science Editors:

Mahalanabis D. Multilevel Resistance Programming in Conductive Bridge Resistive Memory. [Doctoral Dissertation]. Arizona State University; 2015. Available from: http://repository.asu.edu/items/36417


Universidade do Rio Grande do Sul

7. Susin, Eduarda Demori. Plasticidade sináptica e homeostase intrínseca em uma rede neural in silico : propriedades globais e de resposta a estímulos.

Degree: 2016, Universidade do Rio Grande do Sul

Recentemente observou-se experimentalmente, Johnson et al. (2010), que fatias organotípicas corticais de rato são capazes de completar padrões espaço-temporais, após serem treinadas. Embora se especule… (more)

Subjects/Keywords: Biofísica; Integrate-and-fire; Redes neurais; STDP; Homeostase; Intrinsic homeostasis; Signal propagation; Simulação computacional; Local connections; Random connections; Learning; Spatiotemporal processing

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APA (6th Edition):

Susin, E. D. (2016). Plasticidade sináptica e homeostase intrínseca em uma rede neural in silico : propriedades globais e de resposta a estímulos. (Thesis). Universidade do Rio Grande do Sul. Retrieved from http://hdl.handle.net/10183/143172

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):

Susin, Eduarda Demori. “Plasticidade sináptica e homeostase intrínseca em uma rede neural in silico : propriedades globais e de resposta a estímulos.” 2016. Thesis, Universidade do Rio Grande do Sul. Accessed December 05, 2019. http://hdl.handle.net/10183/143172.

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

MLA Handbook (7th Edition):

Susin, Eduarda Demori. “Plasticidade sináptica e homeostase intrínseca em uma rede neural in silico : propriedades globais e de resposta a estímulos.” 2016. Web. 05 Dec 2019.

Vancouver:

Susin ED. Plasticidade sináptica e homeostase intrínseca em uma rede neural in silico : propriedades globais e de resposta a estímulos. [Internet] [Thesis]. Universidade do Rio Grande do Sul; 2016. [cited 2019 Dec 05]. Available from: http://hdl.handle.net/10183/143172.

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

Council of Science Editors:

Susin ED. Plasticidade sináptica e homeostase intrínseca em uma rede neural in silico : propriedades globais e de resposta a estímulos. [Thesis]. Universidade do Rio Grande do Sul; 2016. Available from: http://hdl.handle.net/10183/143172

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


University of California – San Diego

8. Umbria Pedroni, Bruno. Boltzmann Energetics and Temporal Dynamics of Learning Neuromorphic Systems.

Degree: Bioengineering, 2019, University of California – San Diego

 The brain's cognitive power does not arise on exacting digital precision in high-performance computing, but emerges from an extremely efficient and resilient collective form of… (more)

Subjects/Keywords: Artificial intelligence; Neurosciences; Computer engineering; artificial neural network; Boltzmann; Neuromorphic; spiking neural network; STDP; synaptic connectivity

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APA (6th Edition):

Umbria Pedroni, B. (2019). Boltzmann Energetics and Temporal Dynamics of Learning Neuromorphic Systems. (Thesis). University of California – San Diego. Retrieved from http://www.escholarship.org/uc/item/5d83n1x2

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):

Umbria Pedroni, Bruno. “Boltzmann Energetics and Temporal Dynamics of Learning Neuromorphic Systems.” 2019. Thesis, University of California – San Diego. Accessed December 05, 2019. http://www.escholarship.org/uc/item/5d83n1x2.

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

MLA Handbook (7th Edition):

Umbria Pedroni, Bruno. “Boltzmann Energetics and Temporal Dynamics of Learning Neuromorphic Systems.” 2019. Web. 05 Dec 2019.

Vancouver:

Umbria Pedroni B. Boltzmann Energetics and Temporal Dynamics of Learning Neuromorphic Systems. [Internet] [Thesis]. University of California – San Diego; 2019. [cited 2019 Dec 05]. Available from: http://www.escholarship.org/uc/item/5d83n1x2.

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

Council of Science Editors:

Umbria Pedroni B. Boltzmann Energetics and Temporal Dynamics of Learning Neuromorphic Systems. [Thesis]. University of California – San Diego; 2019. Available from: http://www.escholarship.org/uc/item/5d83n1x2

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


EPFL

9. Wozniak, Stanislaw Andrzej. Unsupervised Learning of Phase-Change-Based Neuromorphic Systems.

Degree: 2017, EPFL

 Neuromorphic systems provide brain-inspired methods of computing. In a neuromorphic architecture, inputs are processed by a network of neurons receiving operands through synaptic interconnections, tuned… (more)

Subjects/Keywords: neuromorphic systems; phase-change memristors; spiking neural networks; WTA; STDP; correlation detection; unsupervised online learning; feature extraction; independent components; synaptic competition

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APA (6th Edition):

Wozniak, S. A. (2017). Unsupervised Learning of Phase-Change-Based Neuromorphic Systems. (Thesis). EPFL. Retrieved from http://infoscience.epfl.ch/record/232675

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):

Wozniak, Stanislaw Andrzej. “Unsupervised Learning of Phase-Change-Based Neuromorphic Systems.” 2017. Thesis, EPFL. Accessed December 05, 2019. http://infoscience.epfl.ch/record/232675.

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

MLA Handbook (7th Edition):

Wozniak, Stanislaw Andrzej. “Unsupervised Learning of Phase-Change-Based Neuromorphic Systems.” 2017. Web. 05 Dec 2019.

Vancouver:

Wozniak SA. Unsupervised Learning of Phase-Change-Based Neuromorphic Systems. [Internet] [Thesis]. EPFL; 2017. [cited 2019 Dec 05]. Available from: http://infoscience.epfl.ch/record/232675.

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

Council of Science Editors:

Wozniak SA. Unsupervised Learning of Phase-Change-Based Neuromorphic Systems. [Thesis]. EPFL; 2017. Available from: http://infoscience.epfl.ch/record/232675

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


University of Adelaide

10. Lightheart, Toby Asher. Constructive spiking neural networks for simulations of neuroplasticity.

Degree: 2018, University of Adelaide

 Artificial neural networks are important tools in machine learning and neuroscience; however, a difficult step in their implementation is the selection of the neural network… (more)

Subjects/Keywords: constructive neural networks; spiking neurons; neural simulation; neuroplasticity; STDP; pattern detection; one-shot learning; continual learning

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APA (6th Edition):

Lightheart, T. A. (2018). Constructive spiking neural networks for simulations of neuroplasticity. (Thesis). University of Adelaide. Retrieved from http://hdl.handle.net/2440/115481

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):

Lightheart, Toby Asher. “Constructive spiking neural networks for simulations of neuroplasticity.” 2018. Thesis, University of Adelaide. Accessed December 05, 2019. http://hdl.handle.net/2440/115481.

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

MLA Handbook (7th Edition):

Lightheart, Toby Asher. “Constructive spiking neural networks for simulations of neuroplasticity.” 2018. Web. 05 Dec 2019.

Vancouver:

Lightheart TA. Constructive spiking neural networks for simulations of neuroplasticity. [Internet] [Thesis]. University of Adelaide; 2018. [cited 2019 Dec 05]. Available from: http://hdl.handle.net/2440/115481.

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

Council of Science Editors:

Lightheart TA. Constructive spiking neural networks for simulations of neuroplasticity. [Thesis]. University of Adelaide; 2018. Available from: http://hdl.handle.net/2440/115481

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


Virginia Tech

11. Zhao, Chenyuan. Spike Processing Circuit Design for Neuromorphic Computing.

Degree: PhD, Electrical Engineering, 2019, Virginia Tech

 Neuromorphic computing is a kind of specific electronic system that could mimic biological bodies’ behavior. In most cases, neuromorphic computing system is built with analog… (more)

Subjects/Keywords: Neuromorphic computing; neuron; LIF; temporal encoding; spiking neural network; Inter-spike interval; encoder; decoder; STDP; latency

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APA (6th Edition):

Zhao, C. (2019). Spike Processing Circuit Design for Neuromorphic Computing. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/93591

Chicago Manual of Style (16th Edition):

Zhao, Chenyuan. “Spike Processing Circuit Design for Neuromorphic Computing.” 2019. Doctoral Dissertation, Virginia Tech. Accessed December 05, 2019. http://hdl.handle.net/10919/93591.

MLA Handbook (7th Edition):

Zhao, Chenyuan. “Spike Processing Circuit Design for Neuromorphic Computing.” 2019. Web. 05 Dec 2019.

Vancouver:

Zhao C. Spike Processing Circuit Design for Neuromorphic Computing. [Internet] [Doctoral dissertation]. Virginia Tech; 2019. [cited 2019 Dec 05]. Available from: http://hdl.handle.net/10919/93591.

Council of Science Editors:

Zhao C. Spike Processing Circuit Design for Neuromorphic Computing. [Doctoral Dissertation]. Virginia Tech; 2019. Available from: http://hdl.handle.net/10919/93591

12. Verhoog, M.B. Information processing and storage by the human pyramidal neuron .

Degree: 2016, Vrije Universiteit Amsterdam

Subjects/Keywords: human brain slice electrophysiology neocortex dendritic morphology synaptic plasticity STDP nicotine

…stimulation induces bidirectional STDP-like plasticity in human motor cortex. Front. Hum. Neurosci… …Kerr, J.N.D. (2010). Timing is not everything: Neuromodulation opens the STDP gate… …sensitivity and loss in temporal contrast of STDP by dopaminergic modulation at hippocampal synapses… 

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APA (6th Edition):

Verhoog, M. B. (2016). Information processing and storage by the human pyramidal neuron . (Doctoral Dissertation). Vrije Universiteit Amsterdam. Retrieved from http://hdl.handle.net/1871/54242

Chicago Manual of Style (16th Edition):

Verhoog, M B. “Information processing and storage by the human pyramidal neuron .” 2016. Doctoral Dissertation, Vrije Universiteit Amsterdam. Accessed December 05, 2019. http://hdl.handle.net/1871/54242.

MLA Handbook (7th Edition):

Verhoog, M B. “Information processing and storage by the human pyramidal neuron .” 2016. Web. 05 Dec 2019.

Vancouver:

Verhoog MB. Information processing and storage by the human pyramidal neuron . [Internet] [Doctoral dissertation]. Vrije Universiteit Amsterdam; 2016. [cited 2019 Dec 05]. Available from: http://hdl.handle.net/1871/54242.

Council of Science Editors:

Verhoog MB. Information processing and storage by the human pyramidal neuron . [Doctoral Dissertation]. Vrije Universiteit Amsterdam; 2016. Available from: http://hdl.handle.net/1871/54242


University of Illinois – Urbana-Champaign

13. Duda, Alexander Michael. Towards a neocortically-inspired ab initio cellular model of associative memory.

Degree: PhD, Electrical & Computer Engr, 2015, University of Illinois – Urbana-Champaign

 We are interested in self-organization and adaptation in intelligent systems that are robustly coupled with the real world. Such systems have a variety of sensory… (more)

Subjects/Keywords: Ab Initio Cellular Models; Associative Memory; Attractors; Complex Networks; Emergence; Information-Preserving; Multi-Scale Modeling; Neurorobotics; Nonlinear Dynamics; Real-World Coupling; Spiking Neural Networks; Spike-timing Dependent Plasticity; Spike-timing Dependent Plasticity (STDP) Learning; Topological Adaptation

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APA (6th Edition):

Duda, A. M. (2015). Towards a neocortically-inspired ab initio cellular model of associative memory. (Doctoral Dissertation). University of Illinois – Urbana-Champaign. Retrieved from http://hdl.handle.net/2142/78735

Chicago Manual of Style (16th Edition):

Duda, Alexander Michael. “Towards a neocortically-inspired ab initio cellular model of associative memory.” 2015. Doctoral Dissertation, University of Illinois – Urbana-Champaign. Accessed December 05, 2019. http://hdl.handle.net/2142/78735.

MLA Handbook (7th Edition):

Duda, Alexander Michael. “Towards a neocortically-inspired ab initio cellular model of associative memory.” 2015. Web. 05 Dec 2019.

Vancouver:

Duda AM. Towards a neocortically-inspired ab initio cellular model of associative memory. [Internet] [Doctoral dissertation]. University of Illinois – Urbana-Champaign; 2015. [cited 2019 Dec 05]. Available from: http://hdl.handle.net/2142/78735.

Council of Science Editors:

Duda AM. Towards a neocortically-inspired ab initio cellular model of associative memory. [Doctoral Dissertation]. University of Illinois – Urbana-Champaign; 2015. Available from: http://hdl.handle.net/2142/78735


Arizona State University

14. Sivaraj, Mahraj. STDP Implementation Using CBRAM Devices in CMOS.

Degree: Electrical Engineering, 2015, Arizona State University

Subjects/Keywords: Electrical engineering; Adaptive systems; Conductive Bridge RAM (CBRAM); Learning systems; Memristor; Spike-Timing Dependent Plasticity (STDP); Spiking Neural Networks

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APA (6th Edition):

Sivaraj, M. (2015). STDP Implementation Using CBRAM Devices in CMOS. (Masters Thesis). Arizona State University. Retrieved from http://repository.asu.edu/items/34779

Chicago Manual of Style (16th Edition):

Sivaraj, Mahraj. “STDP Implementation Using CBRAM Devices in CMOS.” 2015. Masters Thesis, Arizona State University. Accessed December 05, 2019. http://repository.asu.edu/items/34779.

MLA Handbook (7th Edition):

Sivaraj, Mahraj. “STDP Implementation Using CBRAM Devices in CMOS.” 2015. Web. 05 Dec 2019.

Vancouver:

Sivaraj M. STDP Implementation Using CBRAM Devices in CMOS. [Internet] [Masters thesis]. Arizona State University; 2015. [cited 2019 Dec 05]. Available from: http://repository.asu.edu/items/34779.

Council of Science Editors:

Sivaraj M. STDP Implementation Using CBRAM Devices in CMOS. [Masters Thesis]. Arizona State University; 2015. Available from: http://repository.asu.edu/items/34779

15. Zhang, Xu. Indirect Training Algorithms for Spiking Neural Networks based on Spiking Timing Dependent Plasticity and Their Applications .

Degree: 2017, Duke University

  Spiking neural networks have been used to investigate the mechanisms of processing in biological neural circuits or to propose hypotheses that can be tested… (more)

Subjects/Keywords: Artificial intelligence; Neurosciences; Robotics; Indirect Training; Learning Mechanism; Neurorobotics; Robotics; Spiking Neural Networks; STDP

…Spike Timing-Dependent Plasticity (STDP) . . . . . . . . . . . . . . 28 2.4.1… …Implement STDP using Local Variables . . . . . . . . . . . . . 31 Discussion… …respectively. . . . . . . . . . . . . . . . . . . . . . . . . . 30 2.11 STDP learning scheme… …indirect ReSuMe under different STDP parameters… …101 5.9 Time cost analysis of indirect ReSuMe under different STDP parameters.102 xv… 

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

APA (6th Edition):

Zhang, X. (2017). Indirect Training Algorithms for Spiking Neural Networks based on Spiking Timing Dependent Plasticity and Their Applications . (Thesis). Duke University. Retrieved from http://hdl.handle.net/10161/14362

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):

Zhang, Xu. “Indirect Training Algorithms for Spiking Neural Networks based on Spiking Timing Dependent Plasticity and Their Applications .” 2017. Thesis, Duke University. Accessed December 05, 2019. http://hdl.handle.net/10161/14362.

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

MLA Handbook (7th Edition):

Zhang, Xu. “Indirect Training Algorithms for Spiking Neural Networks based on Spiking Timing Dependent Plasticity and Their Applications .” 2017. Web. 05 Dec 2019.

Vancouver:

Zhang X. Indirect Training Algorithms for Spiking Neural Networks based on Spiking Timing Dependent Plasticity and Their Applications . [Internet] [Thesis]. Duke University; 2017. [cited 2019 Dec 05]. Available from: http://hdl.handle.net/10161/14362.

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

Council of Science Editors:

Zhang X. Indirect Training Algorithms for Spiking Neural Networks based on Spiking Timing Dependent Plasticity and Their Applications . [Thesis]. Duke University; 2017. Available from: http://hdl.handle.net/10161/14362

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

.