C++ Neural Networks and Fuzzy Logic: Preface

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Image compression. G.W. Cottrell, P. Munro, and D. Zipser used backpropagation to compress

images with the result of an 8:1 compression ratio. They used standard backpropagation with 64 input

neurons (8×8 pixels), 16 hidden neurons, and 64 output neurons equal to the inputs. This is called

self−supervised backpropagation and represents an autoassociative network. The compressed signal

is taken from the hidden layer. The input to hidden layer comprised the compressor, while the hidden

to output layer forms a decompressor.