Description: 1. Introduction.- 1.1 Overview of Neural Architectures.- 1.2 VLSI Neural Network Design Methodology.- 2. VLSI Hopfield Networks.- 2.1 Circuit Dynamics of Hopfield Networks.- 2.2 Existence of Local Minima.- 2.3 Elimination of Local Minima.- 2.4 Neural-Based A/D Converter Without Local Minima.- 2.5 Traveling Salesman Problem.- 3. Hardware Annealing Theory.- 3.1 Simulated Annealing in Software Computation.- 3.2 Hardware Annealing.- 3.3 Application to the Neural-Based A/D Converter.- 4. Programmable Synapses and Gain-Adjustable Neurons.- 4.1 Compact and Programmable Neural Chips.- 4.2 Medium-Term and Long-Term Storage of Synapse Weight.- 5. System Integration for VLSI Neurocomputing.- 5.1 System Module Using Programmable Neural Chip.- 5.2 Application Examples.- 6. Alternative VLSI Neural Chips.- 6.1 Neural Sensory Chips.- 6.2 Various Analog Neural Chips.- 6.3 Various Digital Neural Chips.- 7. Conclusions and Future Work.- Appendixes.

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