Neural Networks for Vision, Speech, and Natural Language

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This inaugural volume in an important new Chapman & Hall series is written by researchers at British Telecommunications 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. It also includes sections on implementation, which discuss some approaches to hardware realization; and architectures, some approaches to hardware realization; and architectures, which describe new ideas and algorithms. Co-published in the US (and distributed in the US) by VNR. Annotation c. Book News, Inc., Portland, OR (
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Product Details

Table of Contents

Introduction: neural networks for vision, speech and natural language 1
Pt. 1 Vision
Neural networks for vision: an introduction 5
1 Image feature location in multi-resolution images using a hierarchy of multilayer perceptrons 13
2 Training multilayer perceptrons for facial feature location: a case study 30
3 The detection of eyes in facial images using radial basis functions 50
4 A neural network feature detector using a multi-resolution pyramid 65
5 Training and testing of neural net window operators on spatiotemporal image sequences 93
6 Image classification using Gabor representations with a neural net 112
Pt. 2 Speech
Neural networks for speech processing: an introduction 129
7 Spoken alphabet recognition using multilayer perceptrons 135
8 Speaker independent vowel recognition 148
9 Dissection of perceptron structures in speech and speaker recognition 160
10 Segmental sub-word unit classification using a multilayer perceptron 177
Pt. 3 Natural Language
Connectionist natural language processing: an introduction 193
11 A single layer higher order neural net and its applications to context free grammar recognition 203
12 Functional compositionality and soft preference rules 235
13 Applications of multilayer perceptrons in text-to-speech synthesis systems 256
Pt. 4 Implementation
Hardware implementation of neural networks: an introduction 289
14 Finite wordlength, integer arithmetic multilayer perceptron modelling for hardware realization 293
15 A VSLI architecture for implementing neural networks with on-chip backpropagation learning 312
16 An opto-electronic neural network processor 330
Pt. 5 Architectures
Architectures: an introduction 349
17 A dynamic topology net 353
18 The stochastic search network 370
19 Node sequence networks 388
20 Some dynamical properties of neural networks 410
Index 439
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