The revitalization of neural network research in the past few years has already had a great impact on research and development in pattern recognition and artificial intelligence. Although neural network functions are not limited to pattern recognition, there is no doubt that a renewed progress in pattern recognition and its applications now critically depends on neural networks. This volume specially brings together outstanding original research papers in the area and aims to help the continued progress in pattern recognition and its applications.Contents:Introduction (C H Chen)Combined Neural-Net/Knowledge-Based Adaptive Systems for Large Scale Dynamic Control (A D C Holden & S C Suddarth)A Connectionist Incremental Expert System Combining Production Systems and Associative Memory (H F Yin & P Liang)Optimal Hidden Units for Two-Layer Nonlinear Feedforward Networks (T D Sanger)An Incremental Fine Adjustment Algorithm for the Design of Optimal Interpolating Networks (S-K Sin & R J P deFigueiredo)On the Asymptotic Properties of Recurrent Neural Networks for Optimization (J Wang)A Real-Time Image Segmentation System Using a Connectionist Classifier Architecture (W E Blanz & S L Gish)Segmentation of Ultrasonic Images with Neural Networks (R H Silverman)Connectionist Model Binarization (N Babaguchi, et al.)An Assessment of Neural Network Technology's on Automatic Active Sonar Classifier Development (T B Haley)On the Relationships between Statistical Pattern Recognition and Artificial Neural Networks (C H Chen)Readership: Computer scientists and engineers.Key Features:Broad range of topicsAuthors are all experts in their fieldsArticles have all been commissioned and edited to appeal to both specialists and non-specialists