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Analog VLSI Circuits for the Perception of Visual Motion

Book Description

Although it is now possible to integrate many millions of transistors on a single chip, traditional digital circuit technology is now reaching its limits, facing problems of cost and technical efficiency when scaled down to ever-smaller feature sizes. The analysis of biological neural systems, especially for visual processing, has allowed engineers to better understand how complex networks can effectively process large amounts of information, whilst dealing with difficult computational challenges.

Analog and parallel processing are key characteristics of biological neural networks. Analog VLSI circuits using the same features can therefore be developed to emulate brain-style processing. Using standard CMOS technology, they can be cheaply manufactured, permitting efficient industrial and consumer applications in robotics and mobile electronics.

This book explores the theory, design and implementation of analog VLSI circuits, inspired by visual motion processing in biological neural networks. Using a novel approach pioneered by the author himself, Stocker explains in detail the construction of a series of electronic chips, providing the reader with a valuable practical insight into the technology.

Analog VLSI Circuits for the Perception of Visual Motion:

  • analyses the computational problems in visual motion perception;

  • examines the issue of optimization in analog networks through high level processes such as motion segmentation and selective attention;

  • demonstrates network implementation in analog VLSI CMOS technology to provide computationally efficient devices;

  • sets out measurements of final hardware implementation;

  • illustrates the similarities of the presented circuits with the human visual motion perception system;

  • includes an accompanying website with video clips of circuits under real-time visual conditions and additional supplementary material.

With a complete review of all existing neuromorphic analog VLSI systems for visual motion sensing, Analog VLSI Circuits for the Perception of Visual Motion is a unique reference for advanced students in electrical engineering, artificial intelligence, robotics and computational neuroscience. It will also be useful for researchers, professionals, and electronics engineers working in the field.

Table of Contents

  1. Cover Page
  2. Title Page
  3. Copyright
  4. Last Quote
  5. Contents
  6. Foreword
  7. Preface
  8. 1: Introduction
    1. 1.1 Artificial Autonomous Systems
    2. 1.2 Neural Computation and Analog Integrated Circuits
  9. 2: Visual Motion Perception
    1. 2.1 Image Brightness
    2. 2.2 Correspondence Problem
    3. 2.3 Optical Flow
    4. 2.4 Matching Models
    5. 2.5 Flow Models
    6. 2.6 Outline for a Visual Motion Perception System
    7. 2.7 Review of aVLSI Implementations
  10. 3: Optimization Networks
    1. 3.1 Associative Memory and Optimization
    2. 3.2 Constraint Satisfaction Problems
    3. 3.3 Winner-takes-all Networks
    4. 3.4 Resistive Network
  11. 4: Visual Motion Perception Networks
    1. 4.1 Model for Optical Flow Estimation
    2. 4.2 Network Architecture
    3. 4.3 Simulation Results for Natural Image Sequences
    4. 4.4 Passive Non-linear Network Conductances
    5. 4.5 Extended Recurrent Network Architectures
    6. 4.6 Remarks
  12. 5: Analog VLSI Implementation
    1. 5.1 Implementation Substrate
    2. 5.2 Phototransduction
    3. 5.3 Extraction of the Spatio-temporal Brightness Gradients
    4. 5.4 Single Optical Flow Unit
    5. 5.5 Layout
  13. 6: Smooth Optical Flow Chip
    1. 6.1 Response Characteristics
    2. 6.2 Intersection-of-constraints Solution
    3. 6.3 Flow Field Estimation
    4. 6.4 Device Mismatch
    5. 6.5 Processing Speed
    6. 6.6 Applications
  14. 7: Extended Network Implementations
    1. 7.1 Motion Segmentation Chip
    2. 7.2 Motion Selection Chip
  15. 8: Comparison to Human Motion Vision
    1. 8.1 Human vs. Chip Perception
    2. 8.2 Computational Architecture
    3. 8.3 Remarks
  16. Appendix A: Variational Calculus
    1. A.1 Optimization Problem
    2. A.2 Well-posed
    3. A.3 Convexity
    4. A.4 Global Solution with Strictly Convex Integrand
  17. Appendix B: Simulation Methods
    1. B.1 Spatio-temporal Gradient Estimation
    2. B.2 Image Sequences
  18. Appendix C: Transistors and Basic Circuits
    1. C.1 Large-signal MOSFET Model
    2. C.2 Differential Pair Circuit
    3. C.3 Transconductance Amplifiers
    4. C.4 References
  19. Appendix D: Process Parameters and Chips Specifications
    1. D.1 AMS 0.8 μ m BiCMOS Process
    2. D.2 Chip Specifications
  20. References
  21. Index