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FPGA Implementations of Neural Networks

Overview of attention for book
FPGA Implementations of Neural Networks
Springer US

Table of Contents

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    Book Overview
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    Chapter 1 FPGA Neurocomputers
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    Chapter 2 On the Arithmetic Precision for Implementing Back-Propagation Networks on FPGA: A Case Study
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    Chapter 3 FPNA: Concepts and Properties
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    Chapter 4 FPNA: Applications and Implementations
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    Chapter 5 Back-Propagation Algorithm Achieving 5 Gops on the Virtex-E
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    Chapter 6 FPGA Implementation of Very Large Associative Memories
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    Chapter 7 FPGA Implementations of Neocognitrons
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    Chapter 8 Self Organizing Feature Map for Color Quantization on FPGA
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    Chapter 9 Implementation of Self-Organizing Feature Maps in Reconfigurable Hardware
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    Chapter 10 FPGA Implementation of a Fully and Partially Connected MLP
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    Chapter 11 FPGA Implementation of Non-Linear Predictors
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    Chapter 12 The REMAP Reconfigurable Architecture: A Retrospective
Attention for Chapter 8: Self Organizing Feature Map for Color Quantization on FPGA
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