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OverviewThis volume contains a collection of papers presented at the 4th Neural Computation and Psychology Workshop, held in London from 7-11 April 1997. The theme of the workshop was: Connectionist Representations: Theory and Practice which covers many importan t issues ranging from the philosophical (such as the grounding problem), and the physiological (what can connectionist representations tell us about the real neural system?), to the technical (what is needed in order to get specific models to work?). The topic is one of increasing importance within Neural Computing and covers issues of interest to researchers from a wide range of backgrounds including: artificial intelligence, applied mathematics, cognitive science, computer science, neurobiology, phi losophy and psychology. In providing a comprehensive overview of this topic it provides an invaluable contribution to the Perspectives in Neural Computing series. Full Product DetailsAuthor: John A: Bullinaria , David W. Glasspool , George Houghton , G. Houghton (all of University of London)Publisher: Springer-Verlag Berlin and Heidelberg GmbH & Co. KG Imprint: Springer-Verlag Berlin and Heidelberg GmbH & Co. K Edition: Edition. ed. Dimensions: Width: 15.50cm , Height: 1.90cm , Length: 23.50cm Weight: 0.560kg ISBN: 9783540762089ISBN 10: 3540762086 Pages: 343 Publication Date: 29 October 1997 Audience: College/higher education , Professional and scholarly , Postgraduate, Research & Scholarly , Professional & Vocational Format: Paperback Publisher's Status: Active Availability: Out of stock  The supplier is temporarily out of stock of this item. It will be ordered for you on backorder and shipped when it becomes available. Table of ContentsRepresentational Issues for Connectionist Psychological Models.- Some Advantages of Localist over Distributed Representations.- Distributed Representations in Radial Basis Function Networks.- A Unified Framework For Connectionist Models.- Separability is a Learner's Best Friend.- A Generative Learning Algorithm that Uses Structural Knowledge of the Input Domain Yields a Better Multi-Layer Perceptron.- Improving Learning and Generalization in Neural Networks Through the Acquisition of Multiple Related Functions.- Representation in Vision and Audition.- Objective Functions for Topography: A Comparison of Optimal Maps.- Testing Principal Component Representations for Faces.- Selection for Object Identification: Modelling Emergent Attentional Processes in Normality and Pathology.- Extracting Features from the Short-Term Time Structure of Cochlear Filtered Sound.- Representation in Working Memory and Attention.- Representational Issues in Neural Systems: Example from a Neural Network Model of Set-Shifting Paradigm Experiments.- Models of Coupled Anterior Working Memories for Frontal Tasks.- A Neurobiologically Inspired Model of Working Memory Based on Neuronal Synchrony and Rhythmicity.- Neural Networks and the Emergence of Consciousness.- Selective Memory Loss in Aphasics: An Insight from Pseudo-Recurrent Connectionist Networks.- Lexical/Semantic Representations.- Extracting Semantic Representations from Large Text Corpora.- Modelling Lexical Decision Using Corpus Derived Semantic Representations in a Connectionist Network.- Semantic Representation and Priming in a Self-Organising Lexicon.- Distributed Representations and the Bilingual Lexicon: One Store or Two?.- Recognising Embedded Words in Connected Speech: Context and Competition.- The Representation of Serial Order.- Dynamic Representation of Structural Constraints in Models of Serial Behaviour.- Representations of Serial Order.- To Repeat or Not to Repeat: The Time Course of Response Suppression in Sequential Behaviour.- A Localist Implementation of the Primacy Model of Immediate Serial Recall.- Connectionist Symbol Processing with Causal Representations.- Author Index.ReviewsAuthor InformationTab Content 6Author Website:Countries AvailableAll regions |
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