Books in Neural networks

Advanced Neural Computers

1st Edition
June 28, 2014
R. Eckmiller
English
eBook
9 7 8 1 4 8 3 2 9 4 2 7 8

This book is the outcome of the International Symposium on Neural Networks for Sensory and Motor Systems (NSMS) held in March 1990 in the FRG. The NSMS symposium assembled 45 invited experts from Europe, America and Japan representing the fields of Neuroinformatics, Computer Science, Computational Neuroscience, and Neuroscience.As a rapidly-published report on the state of the art in Neural Computing it forms a reference book for future research in this highly interdisciplinary field and should prove useful in the endeavor to transfer concepts of brain function and structure to novel neural computers with adaptive, dynamical neural net topologies.A feature of the book is the completeness of the references provided. An alphabetical list of all references quoted in the papers is given, as well as a separate list of general references to help newcomers to the field. A subject index and author index also facilitate access to various details.

Artificial Neural Networks and Statistical Pattern Recognition

1st Edition
Volume 11
June 28, 2014
I.K. Sethi + 1 more
English
eBook
9 7 8 1 4 8 3 2 9 7 8 7 3

With the growing complexity of pattern recognition related problems being solved using Artificial Neural Networks, many ANN researchers are grappling with design issues such as the size of the network, the number of training patterns, and performance assessment and bounds. These researchers are continually rediscovering that many learning procedures lack the scaling property; the procedures simply fail, or yield unsatisfactory results when applied to problems of bigger size. Phenomena like these are very familiar to researchers in statistical pattern recognition (SPR), where the curse of dimensionality is a well-known dilemma. Issues related to the training and test sample sizes, feature space dimensionality, and the discriminatory power of different classifier types have all been extensively studied in the SPR literature. It appears however that many ANN researchers looking at pattern recognition problems are not aware of the ties between their field and SPR, and are therefore unable to successfully exploit work that has already been done in SPR. Similarly, many pattern recognition and computer vision researchers do not realize the potential of the ANN approach to solve problems such as feature extraction, segmentation, and object recognition. The present volume is designed as a contribution to the greater interaction between the ANN and SPR research communities.

Neural Networks

1st Edition
June 28, 2014
E. Gelenbe
English
eBook
9 7 8 1 4 8 3 2 9 7 0 9 5

The present volume is a natural follow-up to Neural Networks: Advances and Applications which appeared one year previously. As the title indicates, it combines the presentation of recent methodological results concerning computational models and results inspired by neural networks, and of well-documented applications which illustrate the use of such models in the solution of difficult problems. The volume is balanced with respect to these two orientations: it contains six papers concerning methodological developments and five papers concerning applications and examples illustrating the theoretical developments. Each paper is largely self-contained and includes a complete bibliography.The methodological part of the book contains two papers on learning, one paper which presents a computational model of intracortical inhibitory effects, a paper presenting a new development of the random neural network, and two papers on associative memory models. The applications and examples portion contains papers on image compression, associative recall of simple typed images, learning applied to typed images, stereo disparity detection, and combinatorial optimisation.

Artificial Neural Networks, 2

1st Edition
June 28, 2014
I. Aleksander + 1 more
English
eBook
9 7 8 1 4 8 3 2 9 8 0 6 1

This two-volume proceedings compilation is a selection of research papers presented at the ICANN-92. The scope of the volumes is interdisciplinary, ranging from the minutiae of VLSI hardware, to new discoveries in neurobiology, through to the workings of the human mind. USA and European research is well represented, including not only new thoughts from old masters but also a large number of first-time authors who are ensuring the continued development of the field.

Adaptive Intelligent Systems

1st Edition
June 28, 2014
Society for Worldwide Society for Worldwide Interban
English
eBook
9 7 8 1 4 8 3 2 9 8 1 5 3

Dedicated to the consideration of advanced I.T. technologies and their financial applications, this volume contains contributions from an international group of system developers and managers from academia, the financial industry and their suppliers: all actively involved in the development and practical introduction of these technologies into banking and financial organisations.Concen... on real experience and present needs, rather than theoretical possibilities or limited prototype applications, it is hoped the publication will give a better insight into advanced I.T. practice and potential as it currently exists and motivate today's developers and researchers.In addition to the discussion of a wide range of technologies and approaches to ensure adaptivity, three other major topics are explored in the book: neural networks, classical software engineering techniques and rule-based systems.

Neurobionics

1st Edition
October 22, 2013
H.-W. Bothe + 2 more
English
eBook
9 7 8 1 4 8 3 2 9 1 5 6 7

The goal of neurobionics is to elaborate methods for the repairment and substitution of impaired functions of the human nervous system. This publication contains contributions from internationally recognized scientists exploring the structure of this novel interdisciplinary research field. The structure consists of theoretical sciences (philosophy, mathematics, neuroinformatics, computational neuroscience), basic biological sciences (molecular biology, cell biology, biological network neuroscience, neurophysiology), technical engineering (microelectronics, micromechanics, robotics, microsystems), and clinical neurosciences (neurodiagnostics, neurology, neurosurgery, neurorehabilitation)... It is hoped the book indicates that a new kind of partnership across these various disciplines is mandatory if emerging problems in the field are to be solved. It also aims to set the coordinates for an international and interdisciplinary research field dealing with a subject intrinsic to man's mind and its biological carrier which may be partially replaced by artificial means in the future.

Neural Networks and Genome Informatics

1st Edition
Volume 1
December 2, 2012
C.H. Wu + 1 more
English
eBook
9 7 8 0 0 8 0 5 3 7 3 7 5

This book is a comprehensive reference in the field of neural networks and genome informatics. The tutorial of neural network foundations introduces basic neural network technology and terminology. This is followed by an in-depth discussion of special system designs for building neural networks for genome informatics, and broad reviews and evaluations of current state-of-the-art methods in the field. This book concludes with a description of open research problems and future research directions.

Neural Networks in Finance

1st Edition
December 22, 2004
Paul D. McNelis
English
eBook
9 7 8 0 0 8 0 4 7 9 6 5 1

This book explores the intuitive appeal of neural networks and the genetic algorithm in finance. It demonstrates how neural networks used in combination with evolutionary computation outperform classical econometric methods for accuracy in forecasting, classification and dimensionality reduction. McNelis utilizes a variety of examples, from forecasting automobile production and corporate bond spread, to inflation and deflation processes in Hong Kong and Japan, to credit card default in Germany to bank failures in Texas, to cap-floor volatilities in New York and Hong Kong.

Kohonen Maps

1st Edition
July 2, 1999
E. Oja + 1 more
English
eBook
9 7 8 0 0 8 0 5 3 5 2 9 6

The Self-Organizing Map, or Kohonen Map, is one of the most widely used neural network algorithms, with thousands of applications covered in the literature. It was one of the strong underlying factors in the popularity of neural networks starting in the early 80's. Currently this method has been included in a large number of commercial and public domain software packages. In this book, top experts on the SOM method take a look at the state of the art and the future of this computing paradigm.The 30 chapters of this book cover the current status of SOM theory, such as connections of SOM to clustering, classification, probabilistic models, and energy functions. Many applications of the SOM are given, with data mining and exploratory data analysis the central topic, applied to large databases of financial data, medical data, free-form text documents, digital images, speech, and process measurements. Biological models related to the SOM are also discussed.

Guide to Neural Computing Applications

1st Edition
January 30, 1998
Lionel Tarassenko
English
eBook
9 7 8 0 0 8 0 5 1 2 6 0 0

Neural networks have shown enormous potential for commercial exploitation over the last few years but it is easy to overestimate their capabilities. A few simple algorithms will learn relationships between cause and effect or organise large volumes of data into orderly and informative patterns but they cannot solve every problem and consequently their application must be chosen carefully and appropriately. This book outlines how best to make use of neural networks. It enables newcomers to the technology to construct robust and meaningful non-linear models and classifiers and benefits the more experienced practitioner who, through over familiarity, might otherwise be inclined to jump to unwarranted conclusions. The book is an invaluable resource not only for those in industry who are interested in neural computing solutions, but also for final year undergraduates or graduate students who are working on neural computing projects. It provides advice which will help make the best use of the growing number of commercial and public domain neural network software products, freeing the specialist from dependence upon external consultants.

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