Neuromorphic Cognitive Systems


Neuromorphic Cognitive Systems
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Neuromorphic Cognitive Systems


Neuromorphic Cognitive Systems
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Author : Qiang Yu
language : en
Publisher: Springer
Release Date : 2017-05-03

Neuromorphic Cognitive Systems written by Qiang Yu and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-05-03 with Technology & Engineering categories.


This book presents neuromorphic cognitive systems from a learning and memory-centered perspective. It illustrates how to build a system network of neurons to perform spike-based information processing, computing, and high-level cognitive tasks. It is beneficial to a wide spectrum of readers, including undergraduate and postgraduate students and researchers who are interested in neuromorphic computing and neuromorphic engineering, as well as engineers and professionals in industry who are involved in the design and applications of neuromorphic cognitive systems, neuromorphic sensors and processors, and cognitive robotics. The book formulates a systematic framework, from the basic mathematical and computational methods in spike-based neural encoding, learning in both single and multi-layered networks, to a near cognitive level composed of memory and cognition. Since the mechanisms for integrating spiking neurons integrate to formulate cognitive functions as in the brain are little understood, studies of neuromorphic cognitive systems are urgently needed. The topics covered in this book range from the neuronal level to the system level. In the neuronal level, synaptic adaptation plays an important role in learning patterns. In order to perform higher-level cognitive functions such as recognition and memory, spiking neurons with learning abilities are consistently integrated, building a system with encoding, learning and memory functionalities. The book describes these aspects in detail.



Brain Inspired Cognitive Systems 2008


Brain Inspired Cognitive Systems 2008
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Author : Amir Hussain
language : en
Publisher: Springer Science & Business Media
Release Date : 2009-12-18

Brain Inspired Cognitive Systems 2008 written by Amir Hussain and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-12-18 with Computers categories.


Brain Inspired Cognitive Systems 2008 (June 24-27, 2008; São Luís, Brazil) brought together leading scientists and engineers who use analytic, syntactic and computational methods both to understand the prodigious processing properties of biological systems and, specifically, of the brain, and to exploit such knowledge to advance computational methods towards ever higher levels of cognitive competence. This book includes the papers presented at four major symposia: Part I - Cognitive Neuroscience Part II - Biologically Inspired Systems Part III - Neural Computation Part IV - Models of Consciousness.



Event Based Neuromorphic Systems


Event Based Neuromorphic Systems
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Author : Shih-Chii Liu
language : en
Publisher: John Wiley & Sons
Release Date : 2015-02-16

Event Based Neuromorphic Systems written by Shih-Chii Liu and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-02-16 with Technology & Engineering categories.


Neuromorphic electronic engineering takes its inspiration from the functioning of nervous systems to build more power efficient electronic sensors and processors. Event-based neuromorphic systems are inspired by the brain's efficient data-driven communication design, which is key to its quick responses and remarkable capabilities. This cross-disciplinary text establishes how circuit building blocks are combined in architectures to construct complete systems. These include vision and auditory sensors as well as neuronal processing and learning circuits that implement models of nervous systems. Techniques for building multi-chip scalable systems are considered throughout the book, including methods for dealing with transistor mismatch, extensive discussions of communication and interfacing, and making systems that operate in the real world. The book also provides historical context that helps relate the architectures and circuits to each other and that guides readers to the extensive literature. Chapters are written by founding experts and have been extensively edited for overall coherence. This pioneering text is an indispensable resource for practicing neuromorphic electronic engineers, advanced electrical engineering and computer science students and researchers interested in neuromorphic systems. Key features: Summarises the latest design approaches, applications, and future challenges in the field of neuromorphic engineering. Presents examples of practical applications of neuromorphic design principles. Covers address-event communication, retinas, cochleas, locomotion, learning theory, neurons, synapses, floating gate circuits, hardware and software infrastructure, algorithms, and future challenges.



Real Time Multi Chip Neural Network For Cognitive Systems


Real Time Multi Chip Neural Network For Cognitive Systems
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Author : Zjajo, Amir
language : en
Publisher: River Publishers
Release Date : 2019-01-25

Real Time Multi Chip Neural Network For Cognitive Systems written by Zjajo, Amir and has been published by River Publishers this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-01-25 with Technology & Engineering categories.


Simulation of brain neurons in real-time using biophysically-meaningful models is a pre-requisite for comprehensive understanding of how neurons process information and communicate with each other, in effect efficiently complementing in-vivo experiments. In spiking neural networks (SNNs), propagated information is not just encoded by the firing rate of each neuron in the network, as in artificial neural networks (ANNs), but, in addition, by amplitude, spike-train patterns, and the transfer rate. The high level of realism of SNNs and more significant computational and analytic capabilities in comparison with ANNs, however, limit the size of the realized networks. Consequently, the main challenge in building complex and biophysically-accurate SNNs is largely posed by the high computational and data transfer demands. Real-Time Multi-Chip Neural Network for Cognitive Systems presents novel real-time, reconfigurable, multi-chip SNN system architecture based on localized communication, which effectively reduces the communication cost to a linear growth. The system use double floating-point arithmetic for the most biologically accurate cell behavior simulation, and is flexible enough to offer an easy implementation of various neuron network topologies, cell communication schemes, as well as models and kinds of cells. The system offers a high run-time configurability, which reduces the need for resynthesizing the system. In addition, the simulator features configurable on- and off-chip communication latencies as well as neuron calculation latencies. All parts of the system are generated automatically based on the neuron interconnection scheme in use. The simulator allows exploration of different system configurations, e.g. the interconnection scheme between the neurons, the intracellular concentration of different chemical compounds (ions), which affect how action potentials are initiated and propagate.



Synaptic Plasticity For Neuromorphic Systems


Synaptic Plasticity For Neuromorphic Systems
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Author : Christian Mayr
language : en
Publisher: Frontiers Media SA
Release Date : 2016-06-26

Synaptic Plasticity For Neuromorphic Systems written by Christian Mayr and has been published by Frontiers Media SA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-06-26 with Neurosciences. Biological psychiatry. Neuropsychiatry categories.


One of the most striking properties of biological systems is their ability to learn and adapt to ever changing environmental conditions, tasks and stimuli. It emerges from a number of different forms of plasticity, that change the properties of the computing substrate, mainly acting on the modification of the strength of synaptic connections that gate the flow of information across neurons. Plasticity is an essential ingredient for building artificial autonomous cognitive agents that can learn to reliably and meaningfully interact with the real world. For this reason, the neuromorphic community at large has put substantial effort in the design of different forms of plasticity and in putting them to practical use. These plasticity forms comprise, among others, Short Term Depression and Facilitation, Homeostasis, Spike Frequency Adaptation and diverse forms of Hebbian learning (e.g. Spike Timing Dependent Plasticity). This special research topic collects the most advanced developments in the design of the diverse forms of plasticity, from the single circuit to the system level, as well as their exploitation in the implementation of cognitive systems.



Advances In Neuromorphic Hardware Exploiting Emerging Nanoscale Devices


Advances In Neuromorphic Hardware Exploiting Emerging Nanoscale Devices
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Author : Manan Suri
language : en
Publisher: Springer
Release Date : 2017-01-21

Advances In Neuromorphic Hardware Exploiting Emerging Nanoscale Devices written by Manan Suri and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-01-21 with Technology & Engineering categories.


This book covers all major aspects of cutting-edge research in the field of neuromorphic hardware engineering involving emerging nanoscale devices. Special emphasis is given to leading works in hybrid low-power CMOS-Nanodevice design. The book offers readers a bidirectional (top-down and bottom-up) perspective on designing efficient bio-inspired hardware. At the nanodevice level, it focuses on various flavors of emerging resistive memory (RRAM) technology. At the algorithm level, it addresses optimized implementations of supervised and stochastic learning paradigms such as: spike-time-dependent plasticity (STDP), long-term potentiation (LTP), long-term depression (LTD), extreme learning machines (ELM) and early adoptions of restricted Boltzmann machines (RBM) to name a few. The contributions discuss system-level power/energy/parasitic trade-offs, and complex real-world applications. The book is suited for both advanced researchers and students interested in the field.



Neuromorphic Engineering Systems And Applications


Neuromorphic Engineering Systems And Applications
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Author : André van Schaik
language : en
Publisher: Frontiers Media SA
Release Date : 2015-07-05

Neuromorphic Engineering Systems And Applications written by André van Schaik and has been published by Frontiers Media SA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-07-05 with Computational neuroscience categories.


Neuromorphic engineering has just reached its 25th year as a discipline. In the first two decades neuromorphic engineers focused on building models of sensors, such as silicon cochleas and retinas, and building blocks such as silicon neurons and synapses. These designs have honed our skills in implementing sensors and neural networks in VLSI using analog and mixed mode circuits. Over the last decade the address event representation has been used to interface devices and computers from different designers and even different groups. This facility has been essential for our ability to combine sensors, neural networks, and actuators into neuromorphic systems. More recently, several big projects have emerged to build very large scale neuromorphic systems. The Telluride Neuromorphic Engineering Workshop (since 1994) and the CapoCaccia Cognitive Neuromorphic Engineering Workshop (since 2009) have been instrumental not only in creating a strongly connected research community, but also in introducing different groups to each other’s hardware. Many neuromorphic systems are first created at one of these workshops. With this special research topic, we showcase the state-of-the-art in neuromorphic systems.



Neuromorphic Intelligence


Neuromorphic Intelligence
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Author : Shuangming Yang
language : en
Publisher: Springer Nature
Release Date :

Neuromorphic Intelligence written by Shuangming Yang and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on with categories.




Neuromorphic Devices For Brain Inspired Computing


Neuromorphic Devices For Brain Inspired Computing
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Author : Qing Wan
language : en
Publisher: John Wiley & Sons
Release Date : 2022-05-16

Neuromorphic Devices For Brain Inspired Computing written by Qing Wan and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-05-16 with Technology & Engineering categories.


Explore the cutting-edge of neuromorphic technologies with applications in Artificial Intelligence In Neuromorphic Devices for Brain-Inspired Computing: Artificial Intelligence, Perception, and Robotics, a team of expert engineers delivers a comprehensive discussion of all aspects of neuromorphic electronics designed to assist researchers and professionals to understand and apply all manner of brain-inspired computing and perception technologies. The book covers both memristic and neuromorphic devices, including spintronic, multi-terminal, and neuromorphic perceptual applications. Summarizing recent progress made in five distinct configurations of brain-inspired computing, the authors explore this promising technology’s potential applications in two specific areas: neuromorphic computing systems and neuromorphic perceptual systems. The book also includes: A thorough introduction to two-terminal neuromorphic memristors, including memristive devices and resistive switching mechanisms Comprehensive explorations of spintronic neuromorphic devices and multi-terminal neuromorphic devices with cognitive behaviors Practical discussions of neuromorphic devices based on chalcogenide and organic materials In-depth examinations of neuromorphic computing and perceptual systems with emerging devices Perfect for materials scientists, biochemists, and electronics engineers, Neuromorphic Devices for Brain-Inspired Computing: Artificial Intelligence, Perception, and Robotics will also earn a place in the libraries of neurochemists, neurobiologists, and neurophysiologists.



Electric Double Layer Coupled Oxide Based Neuromorphic Transistors Studies


Electric Double Layer Coupled Oxide Based Neuromorphic Transistors Studies
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Author : Changjin Wan
language : en
Publisher: Springer
Release Date : 2019-02-04

Electric Double Layer Coupled Oxide Based Neuromorphic Transistors Studies written by Changjin Wan and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-02-04 with Technology & Engineering categories.


This book focuses on essential synaptic plasticity emulations and neuromorphic computing applications realized with the aid of three-terminal synaptic devices based on ion-coupled oxide-based electric-double-layer (EDL) transistors. To replicate the robust, plastic and fault-tolerant computational power of the human brain, the emulation of essential synaptic plasticity and computation of neurons/synapse by electronic devices are generally considered to be key steps. The book shows that the formation of an EDL at the dielectric/channel interface that slightly lags behind the stimuli can be attributed to the electrostatic coupling between ions and electrons; this mechanism underlies the emulation of short-term synaptic behaviors. Furthermore, it demonstrates that electrochemical doping/dedoping processes in the semiconducting channel by penetrated ions from electrolyte can be utilized for the emulation of long-term synaptic behaviors. Lastly, it applies these synaptic transistors in an artificial visual system to demonstrate the potential for constructing neuromorphic systems. Accordingly, the book offers a unique resource on understanding the brain-machine interface, brain-like chips, artificial cognitive systems, etc.