Neural Networks for Vision, Speech and Natural Language

ISBN-13: 9780412430008 / Angielski / Twarda / 1992 / 456 str.

Robert Linggard; R. Linggard; D. J. Myers

Opis

This text is written by researchers at BT Laboratories and at universities who have investigated a set of problems in vision, speech and natural language. It presents a diversity of approaches to the solution of these problems, based on a range of neural network paradigms. The book also includes sections on implementation, which discuss some approaches to hardware realization; and architectures, which describe new ideas and algorithms.

Spis treści

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.