Neural Nets Wirn Vietri 97

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Neural Nets Wirn Vietri 97

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Author : Maria Marinaro
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06

Neural Nets Wirn Vietri 97 written by Maria Marinaro and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Computers categories.

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 98

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Author : Maria Marinaro
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06

Neural Nets Wirn Vietri 98 written by Maria Marinaro and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Computers categories.

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.

Combining Artificial Neural Nets

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Author : Amanda J.C. Sharkey
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06

Combining Artificial Neural Nets written by Amanda J.C. Sharkey and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Computers categories.

The past decade could be seen as the heyday of neurocomputing: in which the capabilities of monolithic nets have been well explored and exploited. The question then is where do we go from here? A logical next step is to examine the potential offered by combinations of artificial neural nets, and it is that step that the chapters in this volume represent. Intuitively, it makes sense to look at combining ANNs. Clearly complex biological systems and brains rely on modularity. Similarly the principles of modularity, and of reliability through redundancy, can be found in many disparate areas, from the idea of decision by jury, through to hardware re dundancy in aeroplanes, and the advantages of modular design and reuse advocated by object-oriented programmers. And it is not surprising to find that the same principles can be usefully applied in the field of neurocomput ing as well, although finding the best way of adapting them is a subject of on-going research.

Artificial Neural Networks In Biomedicine

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Author : Paulo J.G. Lisboa
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06

Artificial Neural Networks In Biomedicine written by Paulo J.G. Lisboa and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Computers categories.

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.

Neural Networks For Conditional Probability Estimation

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Author : Dirk Husmeier
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06

Neural Networks For Conditional Probability Estimation written by Dirk Husmeier and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Computers categories.

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.

4th Neural Computation And Psychology Workshop London 9 11 April 1997

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Author : John A: Bullinaria
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06

4th Neural Computation And Psychology Workshop London 9 11 April 1997 written by John A: Bullinaria and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Computers categories.

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.

Self Organising Neural Networks

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Author : Mark Girolami
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06

Self Organising Neural Networks written by Mark Girolami and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Computers categories.

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.

Artificial Neural Networks In Medicine And Biology

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Author : H. Malmgren
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06

Artificial Neural Networks In Medicine And Biology written by H. Malmgren and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Computers categories.

This book contains the proceedings of the conference ANNIMAB-l, held 13-16 May 2000 in Goteborg, Sweden. The conference was organized by the Society for Artificial Neural Networks in Medicine and Biology (ANNIMAB-S), which was established to promote research within a new and genuinely cross-disciplinary field. Forty-two contributions were accepted for presentation; in addition to these, S invited papers are also included. Research within medicine and biology has often been characterised by application of statistical methods for evaluating domain specific data. The growing interest in Artificial Neural Networks has not only introduced new methods for data analysis, but also opened up for development of new models of biological and ecological systems. The ANNIMAB-l conference is focusing on some of the many uses of artificial neural networks with relevance for medicine and biology, specifically: • Medical applications of artificial neural networks: for better diagnoses and outcome predictions from clinical and laboratory data, in the processing of ECG and EEG signals, in medical image analysis, etc. More than half of the contributions address such clinically oriented issues. • Uses of ANNs in biology outside clinical medicine: for example, in models of ecology and evolution, for data analysis in molecular biology, and (of course) in models of animal and human nervous systems and their capabilities. • Theoretical aspects: recent developments in learning algorithms, ANNs in relation to expert systems and to traditional statistical procedures, hybrid systems and integrative approaches.

Concepts For Neural Networks

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Author : Lawrence J. Landau
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06

Concepts For Neural Networks written by Lawrence J. Landau and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Computers categories.

Concepts for Neural Networks - A Survey provides a wide-ranging survey of concepts relating to the study of neural networks. It includes chapters explaining the basics of both artificial neural networks and the mathematics of neural networks, as well as chapters covering the more philosophical background to the topic and consciousness. There is also significant emphasis on the practical use of the techniques described in the area of robotics. Containing contributions from some of the world's leading specialists in their fields (including Dr. Ton Coolen and Professor Igor Aleksander), this volume will provide the reader with a good, general introduction to the basic concepts needed to understan d and use neural network technology.

Image Processing Using Pulse Coupled Neural Networks

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Author : Thomas Lindblad
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-04-17

Image Processing Using Pulse Coupled Neural Networks written by Thomas Lindblad and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-04-17 with Computers categories.

Pulse-coupled neural networks represent a new and exciting advance in image processing research. When exposed to grey scale or colour images they produce a series of binary pulse images which allow the content of the image to be assessed much more accurately than from the original. In this volume Thomas Lindblad and Jason Kinser provide a much needed introduction to the topic of PCNNs. They review the theoretical foundations, and then look at a number of image processing applications including segmentation, edge extraction, texture extraction, object identification, object isolation, motion processing, foveation, noise suppression and image fusion. They also look at the PCNNs ability to process logical arguments and at how to implement it in specialised hardware. It will be of particular interest to researchers and practitioners working in image processing, especially those involved with medical, military or industrial applications. It will also be of interest to graduate-level students.