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Author: Mariagiovanna Sami
Publisher: North Holland
ISBN:
Category : Computers
Languages : en
Pages : 324
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Book Description
Papers presented within this volume deal with architectures suitable for, and problems typical of, silicon implementation of neural nets. Analog solutions, as opposed to digital ones, are widely advocated as an attractive implementation, given compactness of the obtained architectures, low power consumption, and ease of emulating the analog behaviour of biological networks. Also, a mixed-mode solution, combining the analog/neural and the digital/logical processing aspects is advocated.
Author: Mariagiovanna Sami
Publisher: North Holland
ISBN:
Category : Computers
Languages : en
Pages : 324
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Book Description
Papers presented within this volume deal with architectures suitable for, and problems typical of, silicon implementation of neural nets. Analog solutions, as opposed to digital ones, are widely advocated as an attractive implementation, given compactness of the obtained architectures, low power consumption, and ease of emulating the analog behaviour of biological networks. Also, a mixed-mode solution, combining the analog/neural and the digital/logical processing aspects is advocated.
Author: Ulrich Ramacher
Publisher: Springer Science & Business Media
ISBN: 1461539943
Category : Technology & Engineering
Languages : en
Pages : 346
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Book Description
The early era of neural network hardware design (starting at 1985) was mainly technology driven. Designers used almost exclusively analog signal processing concepts for the recall mode. Learning was deemed not to cause a problem because the number of implementable synapses was still so low that the determination of weights and thresholds could be left to conventional computers. Instead, designers tried to directly map neural parallelity into hardware. The architectural concepts were accordingly simple and produced the so called interconnection problem which, in turn, made many engineers believe it could be solved by optical implementation in adequate fashion only. Furthermore, the inherent fault-tolerance and limited computation accuracy of neural networks were claimed to justify that little effort is to be spend on careful design, but most effort be put on technology issues. As a result, it was almost impossible to predict whether an electronic neural network would function in the way it was simulated to do. This limited the use of the first neuro-chips for further experimentation, not to mention that real-world applications called for much more synapses than could be implemented on a single chip at that time. Meanwhile matters have matured. It is recognized that isolated definition of the effort of analog multiplication, for instance, would be just as inappropriate on the part ofthe chip designer as determination of the weights by simulation, without allowing for the computing accuracy that can be achieved, on the part of the user.
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: 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: Martin T. Hagan
Publisher:
ISBN: 9789812403766
Category : Neural networks (Computer science)
Languages : en
Pages :
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Book Description
Author: Sankar K. Pal
Publisher: World Scientific
ISBN: 981277808X
Category : Computers
Languages : en
Pages : 421
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Book Description
Neural networks (NNs) and systolic arrays (SAs) have many similar features. This volume describes, in a unified way, the basic concepts, theories and characteristic features of integrating or formulating different facets of NNs and SAs, as well as presents recent developments and significant applications. The articles, written by experts from all over the world, demonstrate the various ways this integration can be made to efficiently design methodologies, algorithms and architectures, and also implementations, for NN applications. The book will be useful to graduate students and researchers in many related areas, not only as a reference book but also as a textbook for some parts of the curriculum. It will also benefit researchers and practitioners in industry and R&D laboratories who are working in the fields of system design, VLSI, parallel processing, neural networks, and vision.
Author: E R Caianiello
Publisher: World Scientific
ISBN: 9814555789
Category :
Languages : en
Pages : 396
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Book Description
Organized and supported by IIASS and other Italian institutions, this Workshop in Vietri sul Mare has now become a permanent annual event. The aim is to foster closer links among all groups and individuals working in Europe in this inter- and multi-disciplinary area. Topics cover models, architectures and applications.
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: F. Distante
Publisher:
ISBN:
Category :
Languages : en
Pages : 45
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Book Description
Author: I. Aleksander
Publisher: Elsevier
ISBN: 148329806X
Category : Computers
Languages : en
Pages : 879
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Book Description
This two-volume proceedings compilation is a selection of research papers presented at the ICANN-92. The scope of the volumes is interdisciplinary, ranging from the minutiae of VLSI hardware, to new discoveries in neurobiology, through to the workings of the human mind. USA and European research is well represented, including not only new thoughts from old masters but also a large number of first-time authors who are ensuring the continued development of the field.
