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Neuromorphic Systems Engineering: Neural Networks in Silicon

✍ Scribed by Richard F. Lyon (auth.), Tor Sverre Lande (eds.)


Publisher
Springer US
Year
1998
Tongue
English
Leaves
461
Series
The Springer International Series in Engineering and Computer Science 447
Edition
1
Category
Library

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✦ Synopsis


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 Β£/LISTΒ£
    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.

  • ✦ Table of Contents


    Front Matter....Pages i-xvii
    Front Matter....Pages 1-1
    Filter Cascades as Analogs of the Cochlea....Pages 3-18
    An Analogue VLSI Model of Active Cochlea....Pages 19-47
    A Low-Power Wide-Dynamic-Range Analog VLSI Cochlea....Pages 49-103
    Speech Recognition Experiments with Silicon Auditory Models....Pages 105-126
    Front Matter....Pages 127-127
    The Retinomorphic Approach: Pixel-Parallel Adaptive Amplification, Filtering, and Quantization....Pages 129-150
    Analog VLSI Excitatory Feedback Circuits for Attentional Shifts and Tracking....Pages 151-174
    Floating-Gate Circuits for Adaptation of Saccadic Eye Movement Accuracy....Pages 175-189
    Front Matter....Pages 191-191
    Introduction to Neuromorphic Communication....Pages 193-200
    A Pulsed Communication/Computation Framework for Analog VLSI Perceptive Systems....Pages 201-215
    Asynchronous Communication of 2D Motion Information Using Winner-Takes-All Arbitration....Pages 217-227
    Communicating Neuronal Ensembles between Neuromorphic Chips....Pages 229-259
    Front Matter....Pages 261-261
    Introduction: From Neurobiology to Silicon....Pages 263-266
    A Low-Power Wide-Linear-Range Transconductance Amplifier....Pages 267-313
    Floating-Gate MOS Synapse Transistors....Pages 315-337
    Neuromorphic Synapses for Artificial Dendrites....Pages 339-365
    Winner-Take-All Networks with Lateral Excitation....Pages 367-377
    Front Matter....Pages 379-379
    Neuromorphic Learning VLSI Systems: A Survey....Pages 381-408
    Analog VLSI Stochastic Perturbative Learning Architectures....Pages 409-435
    Winner-Takes-All Associative Memory: A Hamming Distance Vector Quantizer....Pages 437-456
    Back Matter....Pages 457-462

    ✦ Subjects


    Circuits and Systems; Electronic and Computer Engineering; Complexity; Computer Science, general


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