Neural Nets WIRN VIETRI-98
Neural Nets WIRN VIETRI-98

Author: Maria Marinaro

Publisher: Springer Science & Business Media

Published: 2012-12-06

Total Pages: 389

ISBN-13: 1447108116

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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.

Neural Nets WIRN Vietri-99
Neural Nets WIRN Vietri-99

Author: Maria Marinaro

Publisher: Springer Science & Business Media

Published: 2012-12-06

Total Pages: 429

ISBN-13: 1447108779

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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-01
Neural Nets WIRN Vietri-01

Author: Roberto Tagliaferri

Publisher: Springer Science & Business Media

Published: 2012-12-06

Total Pages: 336

ISBN-13: 1447102193

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This volume contains the proceedings of the 12th Italian Workshop on Neural Nets WIRN VIETRI-Ol, jointly organized by the International Institute for Advanced Scientific Studies "Eduardo R. Caianiello" (IIASS), the Societa Italiana Reti Neuroniche (SIREN), the IEEE NNC Italian RIG and the Italian SIG of the INNS. Following the tradition of previous years, we invited three foreign scientists to the workshop, Dr. G. Indiveri and Professors A. Roy and R. Sun, who respectively presented the lectures "Computation in Neuromorphic Analog VLSI Systems", "On Connectionism and Rule Extraction", "Beyond Simple Rule Extraction: Acquiring Planning Knowledge from Neural Networks" (the last two papers being part of the special session mentioned below). In addition, a review talk was presented, dealing with a very up-to-date topic: "NeuroJuzzy Approximator based on Mamdani's Model". A large part of the book contains original contributions approved by referees as oral or poster presentations, which have been assembled for reading convenience into three sections: Architectures and Algorithms, Image and Signal Processing, and Applications. The last part of the books contains the papers of the special Session "From Synapses to Rules". Our thanks go to Prof. B. Apolloni, who organized this section. Furthermore, two sections are dedicated to the memory of two great scientists who were friends in life, Professors Mark Aizerman and Eduardo R. Caianiello. The editors would like to thank the invited speakers, the review lecturers and all the contributors whose highly qualified papers helped with the success of the workshop.

Neural Networks for Conditional Probability Estimation
Neural Networks for Conditional Probability Estimation

Author: Dirk Husmeier

Publisher: Springer Science & Business Media

Published: 2012-12-06

Total Pages: 280

ISBN-13: 1447108477

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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.

Combining Artificial Neural Nets
Combining Artificial Neural Nets

Author: Amanda J.C. Sharkey

Publisher: Springer Science & Business Media

Published: 2012-12-06

Total Pages: 300

ISBN-13: 1447107934

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This volume, written by leading researchers, presents methods of combining neural nets to improve their performance. The techniques include ensemble-based approaches, where a variety of methods are used to create a set of different nets trained on the same task, and modular approaches, where a task is decomposed into simpler problems. The techniques are also accompanied by an evaluation of their relative effectiveness and their application to a variety of problems.

Artificial Neural Networks in Biomedicine
Artificial Neural Networks in Biomedicine

Author: Paulo J.G. Lisboa

Publisher: Springer Science & Business Media

Published: 2012-12-06

Total Pages: 290

ISBN-13: 1447104870

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Following the intense research activIties of the last decade, artificial neural networks have emerged as one of the most promising new technologies for improving the quality of healthcare. Many successful applications of neural networks to biomedical problems have been reported which demonstrate, convincingly, the distinct benefits of neural networks, although many ofthese have only undergone a limited clinical evaluation. Healthcare providers and developers alike have discovered that medicine and healthcare are fertile areas for neural networks: the problems here require expertise and often involve non-trivial pattern recognition tasks - there are genuine difficulties with conventional methods, and data can be plentiful. The intense research activities in medical neural networks, and allied areas of artificial intelligence, have led to a substantial body of knowledge and the introduction of some neural systems into clinical practice. An aim of this book is to provide a coherent framework for some of the most experienced users and developers of medical neural networks in the world to share their knowledge and expertise with readers.

Self-Organising Neural Networks
Self-Organising Neural Networks

Author: Mark Girolami

Publisher: Springer Science & Business Media

Published: 2012-12-06

Total Pages: 276

ISBN-13: 1447108256

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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

Author: Achilleas Zapranis

Publisher: Springer Science & Business Media

Published: 2012-12-06

Total Pages: 194

ISBN-13: 1447105591

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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.

ICANN 98
ICANN 98

Author: Lars Niklasson

Publisher: Springer Science & Business Media

Published: 2013-11-11

Total Pages: 1197

ISBN-13: 1447115996

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ICANN, the International Conference on Artificial Neural Networks, is the official conference series of the European Neural Network Society which started in Helsinki in 1991. Since then ICANN has taken place in Brighton, Amsterdam, Sorrento, Paris, Bochum and Lausanne, and has become Europe's major meeting in the field of neural networks. This book contains the proceedings of ICANN 98, held 2-4 September 1998 in Skovde, Sweden. Of 340 submissions to ICANN 98, 180 were accepted for publication and presentation at the conference. In addition, this book contains seven invited papers presented at the conference. A conference of this size is obviously not organized by three individuals alone. We therefore would like to thank the following people and organizations for supporting ICANN 98 in one way or another: • the European Neural Network Society and the Swedish Neural Network Society for their active support in the organization of this conference, • the Programme Committee and all reviewers for the hard and timely work that was required to produce more than 900 reviews during April 1998, • the Steering Committee which met in Skovde in May 1998 for the final selection of papers and the preparation of the conference program, • the other Module Chairs: Bengt Asker (Industry and Research), Harald Brandt (Applications), Anders Lansner (Computational Neuroscience and Brain Theory), Thorsteinn Rognvaldsson (Theory), Noel Sharkey (co chair Autonomous Robotics and Adaptive Behavior), Bertil Svensson (Hardware and Implementations), • the conference secretary, Leila Khammari, and the rest of the

Connectionist Models in Cognitive Neuroscience
Connectionist Models in Cognitive Neuroscience

Author: Dietmar Heinke

Publisher: Springer Science & Business Media

Published: 2012-12-06

Total Pages: 309

ISBN-13: 1447108132

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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.