Neurally Inspired Silicon Learning PDF Download
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Author: Christopher J. Diorio
Publisher:
ISBN:
Category : Electronic dissertations
Languages : en
Pages : 214
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Book Description
Author: Christopher J. Diorio
Publisher:
ISBN:
Category : Electronic dissertations
Languages : en
Pages : 214
Get Book Here
Book Description
Author: G. Cauwenberghs
Publisher: Springer Science & Business Media
ISBN: 9780792385554
Category : Technology & Engineering
Languages : en
Pages : 444
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Book Description
Learning on Silicon combines models of adaptive information processing in the brain with advances in microelectronics technology and circuit design. The premise is to construct integrated systems not only loaded with sufficient computational power to handle demanding signal processing tasks in sensory perception and pattern recognition, but also capable of operating autonomously and robustly in unpredictable environments through mechanisms of adaptation and learning. This edited volume covers the spectrum of Learning on Silicon in five parts: adaptive sensory systems, neuromorphic learning, learning architectures, learning dynamics, and learning systems. The 18 chapters are documented with examples of fabricated systems, experimental results from silicon, and integrated applications ranging from adaptive optics to biomedical instrumentation. As the first comprehensive treatment on the subject, Learning on Silicon serves as a reference for beginners and experienced researchers alike. It provides excellent material for an advanced course, and a source of inspiration for continued research towards building intelligent adaptive machines.
Author: Tor Sverre Lande
Publisher: Springer
ISBN: 0585280010
Category : Technology & Engineering
Languages : en
Pages : 462
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Book Description
Neuromorphic Systems Engineering: Neural Networks in Silicon emphasizes three important aspects of this exciting new research field. The term neuromorphic expresses relations to computational models found in biological neural systems, which are used as inspiration for building large electronic systems in silicon. By adequate engineering, these silicon systems are made useful to mankind. Neuromorphic Systems Engineering: Neural Networks in Silicon provides the reader with a snapshot of neuromorphic engineering today. It is organized into five parts viewing state-of-the-art developments within neuromorphic engineering from different perspectives. Neuromorphic Systems Engineering: Neural Networks in Silicon provides the first collection of neuromorphic systems descriptions with firm foundations in silicon. Topics presented include: large scale analog systems in silicon neuromorphic silicon auditory (ear) and vision (eye) systems in silicon learning and adaptation in silicon merging biology and technology micropower analog circuit design analog memory analog interchipcommunication on digital buses £/LIST£ Neuromorphic Systems Engineering: Neural Networks in Silicon serves as an excellent resource for scientists, researchers and engineers in this emerging field, and may also be used as a text for advanced courses on the subject.
Author: Jonathan Mapelli
Publisher: Frontiers Media SA
ISBN: 2889746089
Category : Science
Languages : en
Pages : 139
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Book Description
Author: Christian Mayr
Publisher: Frontiers Media SA
ISBN: 2889198774
Category : Neurosciences. Biological psychiatry. Neuropsychiatry
Languages : en
Pages : 178
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Book Description
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.
Author: Yanjun Ma
Publisher: Springer
ISBN: 3319483390
Category : Technology & Engineering
Languages : en
Pages : 290
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Book Description
This book shows readers how to design semiconductor devices using the most common and lowest cost logic CMOS processes. Readers will benefit from the author’s extensive, industrial experience and the practical approach he describes for designing efficiently semiconductor devices that typically have to be implemented using specialized processes that are expensive, time-consuming, and low-yield. The author presents an integrated picture of semiconductor device physics and manufacturing techniques, as well as numerous practical examples of device designs that are tried and true.
Author: Bert Moons
Publisher: Springer
ISBN: 3319992236
Category : Technology & Engineering
Languages : en
Pages : 216
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Book Description
This book covers algorithmic and hardware implementation techniques to enable embedded deep learning. The authors describe synergetic design approaches on the application-, algorithmic-, computer architecture-, and circuit-level that will help in achieving the goal of reducing the computational cost of deep learning algorithms. The impact of these techniques is displayed in four silicon prototypes for embedded deep learning. Gives a wide overview of a series of effective solutions for energy-efficient neural networks on battery constrained wearable devices; Discusses the optimization of neural networks for embedded deployment on all levels of the design hierarchy – applications, algorithms, hardware architectures, and circuits – supported by real silicon prototypes; Elaborates on how to design efficient Convolutional Neural Network processors, exploiting parallelism and data-reuse, sparse operations, and low-precision computations; Supports the introduced theory and design concepts by four real silicon prototypes. The physical realization’s implementation and achieved performances are discussed elaborately to illustrated and highlight the introduced cross-layer design concepts.
Author: Mona E. Zaghloul
Publisher: Springer Science & Business Media
ISBN: 1461526809
Category : Technology & Engineering
Languages : en
Pages : 293
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Book Description
When confronted with the hows and whys of nature's computational engines, some prefer to focus upon neural function: addressing issues of neural system behavior and its relation to natural intelligence. Then there are those who prefer the study of the "mechanics" of neural systems: the nuts and bolts of the "wetware": the neurons and synapses. Those who investigate pulse coded implementations ofartificial neural networks know what it means to stand at the boundary which lies between these two worlds: not just asking why natural neural systems behave as they do, but also how they achieve their marvelous feats. The research results presented in this book not only address more conventional abstract notions of neural-like processing, but also the more specific details ofneural-like processors. It has been established for some time that natural neural systems perform a great deal of information processing via electrochemical pulses. Accordingly, pulse coded neural network concepts are receiving increased attention in artificial neural network research. This increased interest is compounded by continuing advances in the field of VLSI circuit design. This is the first time in history in which it is practical to construct networks of neuron-like circuits of reasonable complexity that can be applied to real problems. We believe that the pioneering work in artificial neural systems presented in this book will lead to further advances that will not only be useful in some practical sense, but may also provide some additional insight into the operation of their natural counterparts.
Author: Rahul Sarpeshkar
Publisher: Cambridge University Press
ISBN: 1139485237
Category : Technology & Engineering
Languages : en
Pages : 909
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Book Description
This book provides, for the first time, a broad and deep treatment of the fields of both ultra low power electronics and bioelectronics. It discusses fundamental principles and circuits for ultra low power electronic design and their applications in biomedical systems. It also discusses how ultra energy efficient cellular and neural systems in biology can inspire revolutionary low power architectures in mixed-signal and RF electronics. The book presents a unique, unifying view of ultra low power analog and digital electronics and emphasizes the use of the ultra energy efficient subthreshold regime of transistor operation in both. Chapters on batteries, energy harvesting, and the future of energy provide an understanding of fundamental relationships between energy use and energy generation at small scales and at large scales. A wealth of insights and examples from brain implants, cochlear implants, bio-molecular sensing, cardiac devices, and bio-inspired systems make the book useful and engaging for students and practicing engineers.
Author: National Research Council
Publisher: National Academies Press
ISBN: 030909612X
Category : Science
Languages : en
Pages : 469
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Book Description
Advances in computer science and technology and in biology over the last several years have opened up the possibility for computing to help answer fundamental questions in biology and for biology to help with new approaches to computing. Making the most of the research opportunities at the interface of computing and biology requires the active participation of people from both fields. While past attempts have been made in this direction, circumstances today appear to be much more favorable for progress. To help take advantage of these opportunities, this study was requested of the NRC by the National Science Foundation, the Department of Defense, the National Institutes of Health, and the Department of Energy. The report provides the basis for establishing cross-disciplinary collaboration between biology and computing including an analysis of potential impediments and strategies for overcoming them. The report also presents a wealth of examples that should encourage students in the biological sciences to look for ways to enable them to be more effective users of computing in their studies.
