Introduction; Vision; Neural Networks for Vision: an introduction; Image feature location in multiresolution images using a hierarchy of multilayer perceptrons; Training multilayer perceptrons for facial feature location: a case study; The detection of eyes in facial images using radial basis functions; Training and testing of neural net window operators on spatiotemporal images; A neural network feature detector using a multi-resolution pyramid; Image classification using Gabor representation.Speech; Neural Networks for speech processing: an introduction; Spoken alphabet recognition using multilayer perceptrons; Speaker independent vowel recognition; Dissection of perceptron structures in speech and speaker recognition; Segmental subword unit classification using a multilayer perceptron; Natural language; Connectionist natural language processing: an introduction; A single layer higher-order nueral net and its application to context-free grammer recognition; Functional compositionality and soft preference rules; Application of multilayer perceptrons in text-to-speech synthesis systems. Implementation; Hardware imlementation of neural networks: an introduction; Finite word length MLPs; A VLSI architecture for implementing neural networks with on chip back-propagation learning; An opto-electronic neural network processor; Architecture ; Architecture: an introduction; A dynamic topology net; The stochastic search network; Node sequence networks; Some dynamical properties of neural networks. Index.
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This book is written by researchers at BT Laboratories and at universities who have investigated a set of problems in vision, speech and natural language.
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