4th Neural Computation and Psychology Workshop, London, 9–11 April 1997

4th Neural Computation and Psychology Workshop, London, 9–11 April 1997 PDF Author: John A: Bullinaria
Publisher: Springer Science & Business Media
ISBN: 1447115465
Category : Computers
Languages : en
Pages : 350

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Book Description
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.

4th Neural Computation and Psychology Workshop, London, 9–11 April 1997

4th Neural Computation and Psychology Workshop, London, 9–11 April 1997 PDF Author: John A: Bullinaria
Publisher: Springer Science & Business Media
ISBN: 1447115465
Category : Computers
Languages : en
Pages : 350

Get Book Here

Book Description
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.

Connectionist Models of Learning, Development and Evolution

Connectionist Models of Learning, Development and Evolution PDF Author: Robert M. French
Publisher: Springer Science & Business Media
ISBN: 1447102819
Category : Psychology
Languages : en
Pages : 327

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Book Description
Connectionist Models of Learning, Development and Evolution comprises a selection of papers presented at the Sixth Neural Computation and Psychology Workshop - the only international workshop devoted to connectionist models of psychological phenomena. With a main theme of neural network modelling in the areas of evolution, learning, and development, the papers are organized into six sections: The neural basis of cognition Development and category learning Implicit learning Social cognition Evolution Semantics Covering artificial intelligence, mathematics, psychology, neurobiology, and philosophy, it will be an invaluable reference work for researchers and students working on connectionist modelling in computer science and psychology, or in any area related to cognitive science.

Connectionist Models of Cognition and Perception

Connectionist Models of Cognition and Perception PDF Author: John Andrew Bullinaria
Publisher: World Scientific
ISBN: 981238037X
Category : Psychology
Languages : en
Pages : 316

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Book Description
Connectionist Models of Cognition and Perception collects together refereed versions of twenty-three papers presented at the Seventh Neural Computation and Psychology Workshop (NCPW7). This workshop series is a well-established and unique forum that brings together researchers from such diverse disciplines as artificial intelligence, cognitive science, computer science, neurobiology, philosophy and psychology to discuss their latest work on connectionist modelling in psychology.The articles have the main theme of connectionist modelling of cognition and perception, and are organised into six sections, on: cell assemblies, representation, memory, perception, vision and language. This book is an invaluable resource for researchers interested in neural models of psychological phenomena.

Self-Organising Neural Networks

Self-Organising Neural Networks PDF Author: Mark Girolami
Publisher: Springer Science & Business Media
ISBN: 1447108256
Category : Computers
Languages : en
Pages : 276

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Book Description
The conception of fresh ideas and the development of new techniques for Blind Source Separation and Independent Component Analysis have been rapid in recent years. It is also encouraging, from the perspective of the many scientists involved in this fascinating area of research, to witness the growing list of successful applications of these methods to a diverse range of practical everyday problems. This growth has been due, in part, to the number of promising young and enthusiastic researchers who have committed their efforts to expanding the current body of knowledge within this field of research. The author of this book is among one of their number. I trust that the present book by Dr. Mark Girolami will provide a rapid and effective means of communicating some of these new ideas to a wide international audience and that in turn this will expand further the growth of knowledge. In my opinion this book makes an important contribution to the theory of Independent Component Analysis and Blind Source Separation. This opens a range of exciting methods, techniques and algorithms for applied researchers and practitioner engineers, especially from the perspective of artificial neural networks and information theory. It has been interesting to see how rapidly the scientific literature in this area has grown.

Principles of Neural Model Identification, Selection and Adequacy

Principles of Neural Model Identification, Selection and Adequacy PDF Author: Achilleas Zapranis
Publisher: Springer Science & Business Media
ISBN: 1447105591
Category : Computers
Languages : en
Pages : 194

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Book Description
Neural networks have had considerable success in a variety of disciplines including engineering, control, and financial modelling. However a major weakness is the lack of established procedures for testing mis-specified models and the statistical significance of the various parameters which have been estimated. This is particularly important in the majority of financial applications where the data generating processes are dominantly stochastic and only partially deterministic. Based on the latest, most significant developments in estimation theory, model selection and the theory of mis-specified models, this volume develops neural networks into an advanced financial econometrics tool for non-parametric modelling. It provides the theoretical framework required, and displays the efficient use of neural networks for modelling complex financial phenomena. Unlike most other books in this area, this one treats neural networks as statistical devices for non-linear, non-parametric regression analysis.

Neural Networks for Conditional Probability Estimation

Neural Networks for Conditional Probability Estimation PDF Author: Dirk Husmeier
Publisher: Springer Science & Business Media
ISBN: 1447108477
Category : Computers
Languages : en
Pages : 280

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Book Description
Conventional applications of neural networks usually predict a single value as a function of given inputs. In forecasting, for example, a standard objective is to predict the future value of some entity of interest on the basis of a time series of past measurements or observations. Typical training schemes aim to minimise the sum of squared deviations between predicted and actual values (the 'targets'), by which, ideally, the network learns the conditional mean of the target given the input. If the underlying conditional distribution is Gaus sian or at least unimodal, this may be a satisfactory approach. However, for a multimodal distribution, the conditional mean does not capture the relevant features of the system, and the prediction performance will, in general, be very poor. This calls for a more powerful and sophisticated model, which can learn the whole conditional probability distribution. Chapter 1 demonstrates that even for a deterministic system and 'be nign' Gaussian observational noise, the conditional distribution of a future observation, conditional on a set of past observations, can become strongly skewed and multimodal. In Chapter 2, a general neural network structure for modelling conditional probability densities is derived, and it is shown that a universal approximator for this extended task requires at least two hidden layers. A training scheme is developed from a maximum likelihood approach in Chapter 3, and the performance ofthis method is demonstrated on three stochastic time series in chapters 4 and 5.

Connectionist Models in Cognitive Neuroscience

Connectionist Models in Cognitive Neuroscience PDF Author: Dietmar Heinke
Publisher: Springer Science & Business Media
ISBN: 1447108132
Category : Computers
Languages : en
Pages : 309

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Book Description
1. Introdudion This volume collects together the refereed versions of 25 papers presented at the 5th Neural Computation and Psychology Workshop (NCPW5), held at the University of Birmingham from the 8th until the lOth of September 1998. The NCPW is a well-established, lively forum, which brings together researchers from a range of disciplines (artificial intelligence, mathematics, cognitive science, computer science, neurobiology, philosophy and psychology), all of whom are interested in the application of neurally-inspired (connectionist) models to topics in psychology. The theme of the 5th workshop in the series was Connectionist models in cognitive neuroscience', and the workshop aimed to bring together papers focused on the inter-relations between functional (psychological) accounts of cognition and neural accounts of underlying brain processes, linked by connectionist models. From the very beginnings of modern psychology, with the work of William James and his contemporaries, researchers have believed it important to relate behavioural analyses to neurological underpinnings. However, with the advent of connectionist modelling, where models are at least inspired by neuronal processes, this enterprise has received a new boost. With this volume, we hope that this volume adds one further mosaic stone to this ambitious objective, of unifying functional and neuronal accounts of performance.

Neural Nets WIRN VIETRI-97

Neural Nets WIRN VIETRI-97 PDF Author: Maria Marinaro
Publisher: Springer Science & Business Media
ISBN: 1447115201
Category : Computers
Languages : en
Pages : 338

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Book Description
This volume contains selected papers from WIRN VIETRI-97, the 9th Italian Workshop on Neural Nets, held Vietri sul Mare, Salerno, Italy, from 22-24 May 1997. The papers cover a variety of topics related to neural networks, including pattern recognition, signal processing, theoretical models, applications in science and industry, virtual reality, fuzzy systems, and software algorithms. = By providing the reader with a comprehensive overview of recent research work in this area, the volume makes an invaluab le contribution to the Perspectives in Neural Computing Series. Neural Nets - WIRN VIETRI-97 will provide invaluable reading material for anyone who needs to keep up to date with the latest developments in neural networks and related areas. It will be of particular interest to academic and industrial researchers, and postgraduate and graduate students.

Neural Nets WIRN Vietri-99

Neural Nets WIRN Vietri-99 PDF Author: Maria Marinaro
Publisher: Springer Science & Business Media
ISBN: 1447108779
Category : Computers
Languages : en
Pages : 429

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Book Description
From its early beginnings in the fifties and sixties, the field of neural networks has been steadily developing to become one of the most interdisciplinary areas of research within computer science. This volume contains a selection of papers from WIRN Vietri-99, the 11th Italian Workshop on Neural Nets. This annual event, sponsored, amongst others, by the IEEE Neural Networks Council and the INNS/SIG Italy, brings together the best of research from all over the world. The papers cover a range of topics within neural networks, including pattern recognition, signal and image processing, mathematical models, neuro-fuzzy models and economics applications.

Neural Nets WIRN VIETRI-98

Neural Nets WIRN VIETRI-98 PDF Author: Maria Marinaro
Publisher: Springer Science & Business Media
ISBN: 1447108116
Category : Computers
Languages : en
Pages : 389

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Book Description
From its early beginnings in the fifties and sixties, the field of neural networks has been steadily developing to become one of the most interdisciplinary areas of research within computer science. This volume contains selected papers from WIRN Vietri-98, the 10th Italian Workshop on Neural Nets, 21-23 May 1998, Vietri sul Mare, Salerno, Italy. This annual event, sponsored amongst others by the IEEE Neural Network Council and the INNS/SIG Italy, brings together the best of research from all over the world. The papers cover a range of key topics within neural networks, including pattern recognition, signal processing, hybrid systems, mathematical models, hardware and software design, and fuzzy techniques. It also includes two review talks on a Morpho-Functional Model to Describe Variability Found at Hippocampal Synapses and Neural Networks and Speech Processing. By providing the reader with a comprehensive overview of recent research in this area, the volume makes a valuable contribution to the Perspectives in Neural Computing Series.