{"product_id":"analog-vlsi-circuits-for-the-perception-of-visual-motion-9780470854914","title":"Analog VLSI Circuits for the Perception of Visual","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003eAlthough 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.\u003cbr\u003e\u003cbr\u003e\u003cb\u003eTrade Review\u003c\/b\u003e\u003cbr\u003e\"This new book provides unconventional and fresh perspectives on how to understand perception and build simple artificial perceptual systems using VLSI circuits.\" (\u003ci\u003eThe Neurimorphic Engineer,\u003c\/i\u003e March 2007 \u003cbr\u003e\u003cbr\u003e\u003cb\u003eTable of Contents\u003c\/b\u003e\u003cbr\u003e\u003cb\u003eForeword.\u003c\/b\u003e  \u003cp\u003e\u003cb\u003ePreface.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003e1 Introduction.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e1.1 Artificial Autonomous Systems.\u003c\/p\u003e \u003cp\u003e1.2 Neural Computation and Analog Integrated Circuits.\u003c\/p\u003e \u003cp\u003e\u003cb\u003e2 Visual Motion Perception.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e2.1 Image Brightness.\u003c\/p\u003e \u003cp\u003e2.2 Correspondence Problem.\u003c\/p\u003e \u003cp\u003e2.3 Optical Flow.\u003c\/p\u003e \u003cp\u003e2.4 Matching Models.\u003c\/p\u003e \u003cp\u003e2.4.1 Explicit matching.\u003c\/p\u003e \u003cp\u003e2.4.2 Implicit matching.\u003c\/p\u003e \u003cp\u003e2.5 FlowModels.\u003c\/p\u003e \u003cp\u003e2.5.1 Global motion.\u003c\/p\u003e \u003cp\u003e2.5.2 Local motion.\u003c\/p\u003e \u003cp\u003e2.5.3 Perceptual bias.\u003c\/p\u003e \u003cp\u003e2.6 Outline for a Visual Motion Perception System.\u003c\/p\u003e \u003cp\u003e2.7 Review of aVLSI Implementations.\u003c\/p\u003e \u003cp\u003e\u003cb\u003e3 Optimization Networks.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e3.1 AssociativeMemory and Optimization.\u003c\/p\u003e \u003cp\u003e3.2 Constraint Satisfaction Problems.\u003c\/p\u003e \u003cp\u003e3.3 Winner-takes-all Networks.\u003c\/p\u003e \u003cp\u003e3.3.1 Network architecture.\u003c\/p\u003e \u003cp\u003e3.3.2 Global convergence and gain.\u003c\/p\u003e \u003cp\u003e3.4 Resistive Network.\u003c\/p\u003e \u003cp\u003e\u003cb\u003e4 Visual Motion Perception Networks.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e4.1 Model for Optical Flow Estimation.\u003c\/p\u003e \u003cp\u003e4.1.1 Well-posed optimization problem.\u003c\/p\u003e \u003cp\u003e4.1.2 Mechanical equivalent.\u003c\/p\u003e \u003cp\u003e4.1.3 Smoothness and sparse data.\u003c\/p\u003e \u003cp\u003e4.1.4 Probabilistic formulation.\u003c\/p\u003e \u003cp\u003e4.2 Network Architecture.\u003c\/p\u003e \u003cp\u003e4.2.1 Non-stationary optimization.\u003c\/p\u003e \u003cp\u003e4.2.2 Network conductances.\u003c\/p\u003e \u003cp\u003e4.3 Simulation Results for Natural Image Sequences.\u003c\/p\u003e \u003cp\u003e4.4 Passive Non-linear Network Conductances.\u003c\/p\u003e \u003cp\u003e4.5 Extended Recurrent Network Architectures.\u003c\/p\u003e \u003cp\u003e4.5.1 Motion segmentation.\u003c\/p\u003e \u003cp\u003e4.5.2 Attention and motion selection.\u003c\/p\u003e \u003cp\u003e4.6 Remarks.\u003c\/p\u003e \u003cp\u003e\u003cb\u003e5 Analog VLSI Implementation.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e5.1 Implementation Substrate.\u003c\/p\u003e \u003cp\u003e5.2 Phototransduction.\u003c\/p\u003e \u003cp\u003e5.2.1 Logarithmic adaptive photoreceptor.\u003c\/p\u003e \u003cp\u003e5.2.2 Robust brightness constancy constraint.\u003c\/p\u003e \u003cp\u003e5.3 Extraction of the Spatio-temporal Brightness Gradients.\u003c\/p\u003e \u003cp\u003e5.3.1 Temporal derivative circuits.\u003c\/p\u003e \u003cp\u003e5.3.2 Spatial sampling.\u003c\/p\u003e \u003cp\u003e5.4 Single Optical Flow Unit.\u003c\/p\u003e \u003cp\u003e5.4.1 Wide-linear-range multiplier.\u003c\/p\u003e \u003cp\u003e5.4.2 Effective bias conductance.\u003c\/p\u003e \u003cp\u003e5.4.3 Implementation of the smoothness constraint.\u003c\/p\u003e \u003cp\u003e5.5 Layout.\u003c\/p\u003e \u003cp\u003e\u003cb\u003e6 Smooth Optical Flow Chip.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e6.1 Response Characteristics.\u003c\/p\u003e \u003cp\u003e6.1.1 Speed tuning.\u003c\/p\u003e \u003cp\u003e6.1.2 Contrast dependence.\u003c\/p\u003e \u003cp\u003e6.1.3 Spatial frequency tuning.\u003c\/p\u003e \u003cp\u003e6.1.4 Orientation tuning.\u003c\/p\u003e \u003cp\u003e6.2 Intersection-of-constraints Solution.\u003c\/p\u003e \u003cp\u003e6.3 Flow Field Estimation.\u003c\/p\u003e \u003cp\u003e6.4 DeviceMismatch.\u003c\/p\u003e \u003cp\u003e6.4.1 Gradient offsets.\u003c\/p\u003e \u003cp\u003e6.4.2 Variations across the array.\u003c\/p\u003e \u003cp\u003e6.5 Processing Speed.\u003c\/p\u003e \u003cp\u003e6.6 Applications.\u003c\/p\u003e \u003cp\u003e6.6.1 Sensor modules for robotic applications.\u003c\/p\u003e \u003cp\u003e6.6.2 Human–machine interface.\u003c\/p\u003e \u003cp\u003e\u003cb\u003e7 Extended Network Implementations.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e7.1 Motion Segmentation Chip.\u003c\/p\u003e \u003cp\u003e7.1.1 Schematics of the motion segmentation pixel.\u003c\/p\u003e \u003cp\u003e7.1.2 Experiments and results.\u003c\/p\u003e \u003cp\u003e7.2 Motion Selection Chip.\u003c\/p\u003e \u003cp\u003e7.2.1 Pixel schematics.\u003c\/p\u003e \u003cp\u003e7.2.2 Non-linear diffusion length.\u003c\/p\u003e \u003cp\u003e7.2.3 Experiments and results.\u003c\/p\u003e \u003cp\u003e\u003cb\u003e8 Comparison to Human Motion Vision.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e8.1 Human vs. Chip Perception.\u003c\/p\u003e \u003cp\u003e8.1.1 Contrast-dependent speed perception.\u003c\/p\u003e \u003cp\u003e8.1.2 Bias on perceived direction of motion.\u003c\/p\u003e \u003cp\u003e8.1.3 Perceptual dynamics.\u003c\/p\u003e \u003cp\u003e8.2 Computational Architecture.\u003c\/p\u003e \u003cp\u003e8.3 Remarks.\u003c\/p\u003e \u003cp\u003e\u003cb\u003eAppendix.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003eA Variational Calculus.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003eB Simulation Methods.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003eC Transistors and Basic Circuits.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003eD Process Parameters and Chips Specifications.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003eReferences.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003eIndex.\u003c\/b\u003e\u003c\/p\u003e","brand":"John Wiley \u0026 Sons Inc","offers":[{"title":"Default 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