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Neuromorphic Systems Engineering

Neural Networks in Silicon

  • Book
  • © 1998

Overview

Editors:
  1. Tor Sverre Lande

    1. University of Oslo, Norway

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Part of the book series: The Springer International Series in Engineering and Computer Science (SECS, volume 447)

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Table of contents (19 chapters)

  1. Front Matter

    Pages i-xvii
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  2. Cochlear Systems

    1. Front Matter

      Pages 1-1
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    2. Filter Cascades as Analogs of the Cochlea

      • Richard F. Lyon
      Pages 3-18

    3. An Analogue VLSI Model of Active Cochlea

      • Eric Fragnière, André van Schaik, Eric A. Vittoz
      Pages 19-47

    4. A Low-Power Wide-Dynamic-Range Analog VLSI Cochlea

      • Rahul Sarpeshkar, Richard F. Lyon, Carver Mead
      Pages 49-103

    5. Speech Recognition Experiments with Silicon Auditory Models

      • John Lazzaro, John Wawrzynek
      Pages 105-126

  3. Retinomorphic Systems

    1. Front Matter

      Pages 127-127
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    2. The Retinomorphic Approach: Pixel-Parallel Adaptive Amplification, Filtering, and Quantization

      • Kwabena A. Boahen
      Pages 129-150

    3. Analog VLSI Excitatory Feedback Circuits for Attentional Shifts and Tracking

      • T. G. Morris, S. P. DeWeerth
      Pages 151-174

    4. Floating-Gate Circuits for Adaptation of Saccadic Eye Movement Accuracy

      • Timothy K. Horiuchi, Christof Koch
      Pages 175-189

  4. Neuromorphic Communication

    1. Front Matter

      Pages 191-191
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    2. Introduction to Neuromorphic Communication

      • Tor Sverre Lande
      Pages 193-200

    3. A Pulsed Communication/Computation Framework for Analog VLSI Perceptive Systems

      • Alessandro Mortara
      Pages 201-215

    4. Asynchronous Communication of 2D Motion Information Using Winner-Takes-All Arbitration

      • Zaven Kalayjian, Andreas G. Andreou
      Pages 217-227

    5. Communicating Neuronal Ensembles between Neuromorphic Chips

      • Kwabena A. Boahen
      Pages 229-259

  5. Neuromorphic Technology

    1. Front Matter

      Pages 261-261
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    2. Introduction: From Neurobiology to Silicon

      • Chris Diorio
      Pages 263-266

    3. A Low-Power Wide-Linear-Range Transconductance Amplifier

      • Rahul Sarpeshkar, Richard F. Lyon, Carver Mead
      Pages 267-313

    4. Floating-Gate MOS Synapse Transistors

      • Chris Diorio, Paul Hasler, Bradley A. Minch, Carver Mead
      Pages 315-337

    5. Neuromorphic Synapses for Artificial Dendrites

      • Wayne C. Westerman, David P. M. Northmore, John. G. Elias
      Pages 339-365
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Keywords

About this book

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.

    • Editors and Affiliations

    • University of Oslo, Norway

      Tor Sverre Lande

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