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4th Neural Computation and Psychology Workshop, London, 9–11 April 1997: Connectionist Representations: Perspectives in Neural Computing

Editat de John A: Bullinaria, David W. Glasspool, George Houghton
en Limba Engleză Paperback – 29 oct 1997
This volume collects together refereed versions of twenty-five papers presented at the 4th Neural Computation and Psychology Workshop, held at University College London in April 1997. The "NCPW" workshop series is now well established as a lively forum which brings together researchers from such diverse disciplines as artificial intelligence, mathematics, cognitive science, computer science, neurobiology, philosophy and psychology to discuss their work on connectionist modelling in psychology. The general theme of this fourth workshop in the series was "Connectionist Repre­ sentations", a topic which not only attracted participants from all these fields, but from allover the world as well. From the point of view of the conference organisers focusing on representational issues had the advantage that it immediately involved researchers from all branches of neural computation. Being so central both to psychology and to connectionist modelling, it is one area about which everyone in the field has their own strong views, and the diversity and quality of the presentations and, just as importantly, the discussion which followed them, certainly attested to this.
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Specificații

ISBN-13: 9783540762089
ISBN-10: 3540762086
Pagini: 360
Ilustrații: XIII, 343 p. 37 illus.
Dimensiuni: 155 x 235 x 19 mm
Greutate: 0.5 kg
Ediția:1st Edition.
Editura: SPRINGER LONDON
Colecția Springer
Seria Perspectives in Neural Computing

Locul publicării:London, United Kingdom

Public țintă

Research

Cuprins

Representational 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 SerialOrder.- 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.