Artificial Intelligence IV

Artificial Intelligence IV
Author: P. Jorrand
Publisher: Elsevier
Total Pages: 450
Release: 2016-01-22
Genre: Computers
ISBN: 1483297780

Presenting recent results and ongoing research in Artificial Intelligence, this book has a strong emphasis on fundamental questions in several key areas: programming languages, automated reasoning, natural language processing and computer vision.AI is at the source of major programming language design efforts. Different approaches are described, with some of their most significant results: languages combining logic and functional styles, logic and parallel, functional and parallel, logic with constraints.A central problem in AI is automated reasoning, and formal logic is, historically, at the root of research in this domain. This book presents results in automatic deduction, non-monotonic reasoning, non-standard logic, machine learning, and common-sense reasoning. Proposals for knowledge representation and knowledge engineering are described and the neural net challenger to classical symbolic AI is also defended.Finally, AI systems must be able to interact with their environment in a natural and autonomous way. Natural language processing is an important part of this. Various results are presented in discourse planning, natural language parsing, understanding and generation. The autonomy of a machine for perception of its physical environment is also an AI problem and some research in image processing and computer vision is described.

ICANN ’94

ICANN ’94
Author: Maria Marinaro
Publisher: Springer
Total Pages: 1488
Release: 1994-05-20
Genre: Computers
ISBN: 9783540198871

From its early beginnings in the fifties and sixties the field of neural networks has been steadily growing. The first wave was driven by a handful of pioneers who first discovered analogies between machines and biological systems in communication, control and computing. Technological constraints held back research considerably, but gradually computers have become less expensive and more accessible and software tools inceasingly more powerful. Mathematical techniques, developed by computer-aware people, have steadily accumulated and the second wave has begun. Researchers from such diverse areas as psychology, mathematics, physics, neuroscience and engineering now work together in the neural networking field.

Digital Neural Networks

Digital Neural Networks
Author: Sun Yuan Kung
Publisher: Prentice Hall
Total Pages: 472
Release: 1993
Genre: Computers
ISBN:

Intended for engineers and researchers interested in the applications of neural networks to signal and image processing, this book is theoretically based with emphasis on application and implementation. Coverage includes neural networks for representation, unsupervised networks for association/classification, neural networks for generalization/restoration, neural net and conventional optimization techniques, and special purpose supercomputers for neural nets.

Neural Networks in Financial Engineering

Neural Networks in Financial Engineering
Author: Apostolos-Paul Refenes
Publisher: World Scientific Publishing Company Incorporated
Total Pages: 634
Release: 1996
Genre: Business & Economics
ISBN: 9789810224806

Recoge 50 trabajos de investigación originales agrupados en 6 apartados: Derivados y modelos estructurados; Cambio exterior; Valores y materias primas; Modelos de riesgo y peligro empresarial; Macroeconomía y finanzas al por menor; Estado de la cuestión en metodología.

Neural Networks and Their Applications

Neural Networks and Their Applications
Author: John G. Taylor
Publisher: John Wiley & Sons
Total Pages: 336
Release: 1996
Genre: Computers
ISBN:

Neural networks are one of the fast-growing paradigms for learning systems with a wide variety of potential applications in industry. In particular there are general results which prove the universal applicability of neural networks to many problems. There is also an ever greater understanding of the underlying manner in which tasks such as classification can be solved optimally by this host of techniques. Through the application of ideas of statistics, dynamical systems theory and information theory the methods are likely to become ever more effective for solving problems previously found to be difficult to tackle using standard techniques. This book compares and contrasts the academic theory and the industrial reality, with case studies and latest research findings from international experts. The contributions describe application areas including finance, digital data transmission, hybrid systems, automotive and aerospace industries, pattern analysis in clinical psychiatry, time series prediction, and genetic and neural algorithms. This book demonstrates the vigour and strength of the subject in solving hard problems and as such will be of great interest to all researchers and professionals with an interest in neural networks.

Neural Networks in the Capital Markets

Neural Networks in the Capital Markets
Author: Apostolos-Paul Refenes
Publisher: Wiley
Total Pages: 392
Release: 1995-03-28
Genre: Business & Economics
ISBN: 9780471943648

Based on original papers which represent new and significant research, developments and applications in finance and investment. The author takes a pragmatic view of neural networks, treating them as computationally equivalent to well-understood, non-parametric inference methods in decision science. The author also makes comparisons with established techniques where appropriate.