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视觉感知的模拟超大规模集成电路实现（影印版）
作者：（美）斯多克
出版社：科学
出版时间：2007-01-01
ISBN：9787030182548
定价：¥38.00
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内容简介
计算神经系统科学是一个正在兴起的研究领域，近年来已经成为许多国家政府资助的研究方向，吸引着许多青年研究人员。本书分析了视觉运动感知的计算问题、模拟网络的优化方法等，最有特色处在于从大规模集成电路实现的角度分析了视觉运动处理的原理和算法，可以借助大规模集成电路的高集成度、低成本等优势，进行模拟的并行视觉运动感知。.本书的专业性很强，所涉及的问题非常前沿，属于交叉学科，极具发展潜力，其权威性不言而喻。对于从事神经网络、人工智能、控制理论的等领域的研究者，本书有很大的参考价值。在我国，这方面的研究还处于起步阶段，本书提出的视觉运动集成电路实现方法无疑是一种崭新的思路。...
作者简介
暂缺《视觉感知的模拟超大规模集成电路实现（影印版）》作者简介
目录
Foreword
Preface
1 Introduction
1.1 Artificial Autonomous Systems
1.2 Neural Computation and Analog Integrated Circuits
2 Visual Motion Perception
2.1 Image Brightness
2.2 Correspondence Problem
2.3 Optical Flow
2.4 Matching Models
2.5 Flow Models
2.6 Outline for a Visual Motion Perception System
2.7 Review of a VLSI Implementations
3 Optimization Networks
3.1 Associative Memory and Optimization
3.2 Constraint Satisfaction Problems
3.3 Winner-takes-all Networks
3.4 Resistive Network
4 Visual Motion Perception Networks
4.1 Model for Optical Flow Estimation
4.2 Network Architecture
4.3 Simulation Results for Natural Image Sequences
4.4 Passive Non-linear Network Conducatances
4.5 Extended Recurrent Network Architectures
4.6 Remarks
5 Analog VLSI Implementation
5.1 Implementation Substrate
5.2 Phototransduction
5.3 Extraction of the Spatio-temporal Brightness Gradients
5.4 Single Optical Flow Unit
5.5 Layout
6 Smooth Optical Flow Chip
6.1 Response Characteristics
6.2 Intersection-of-constraints Solution
6.3 Flow Field Estimation
6.4 Device Mismatch
6.5 Processing Speed
6.6 Applications
7 Extended Network Implementations
7.1 Motion Segmentation Chip
7.2 Motion Selection Chip
8 Comparison to Human Motion Vision
8.1 Human vs.Chip Perception
8.2 Computational Architecture
8.3 Remarks
A Variational Calculus
B Simulation Methods
C Transistors and Basic Circuits
D Process Parameters and Chips Specifications
References
Index
Preface
1 Introduction
1.1 Artificial Autonomous Systems
1.2 Neural Computation and Analog Integrated Circuits
2 Visual Motion Perception
2.1 Image Brightness
2.2 Correspondence Problem
2.3 Optical Flow
2.4 Matching Models
2.5 Flow Models
2.6 Outline for a Visual Motion Perception System
2.7 Review of a VLSI Implementations
3 Optimization Networks
3.1 Associative Memory and Optimization
3.2 Constraint Satisfaction Problems
3.3 Winner-takes-all Networks
3.4 Resistive Network
4 Visual Motion Perception Networks
4.1 Model for Optical Flow Estimation
4.2 Network Architecture
4.3 Simulation Results for Natural Image Sequences
4.4 Passive Non-linear Network Conducatances
4.5 Extended Recurrent Network Architectures
4.6 Remarks
5 Analog VLSI Implementation
5.1 Implementation Substrate
5.2 Phototransduction
5.3 Extraction of the Spatio-temporal Brightness Gradients
5.4 Single Optical Flow Unit
5.5 Layout
6 Smooth Optical Flow Chip
6.1 Response Characteristics
6.2 Intersection-of-constraints Solution
6.3 Flow Field Estimation
6.4 Device Mismatch
6.5 Processing Speed
6.6 Applications
7 Extended Network Implementations
7.1 Motion Segmentation Chip
7.2 Motion Selection Chip
8 Comparison to Human Motion Vision
8.1 Human vs.Chip Perception
8.2 Computational Architecture
8.3 Remarks
A Variational Calculus
B Simulation Methods
C Transistors and Basic Circuits
D Process Parameters and Chips Specifications
References
Index
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