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Download Neural Networks: Advances and Applications fb2

by Erol Gelenbe
Download Neural Networks: Advances and Applications fb2
Computer Science
  • Author:
    Erol Gelenbe
  • ISBN:
    0444885331
  • ISBN13:
    978-0444885333
  • Genre:
  • Publisher:
    North-Holland (March 1, 1991)
  • Pages:
    282 pages
  • Subcategory:
    Computer Science
  • Language:
  • FB2 format
    1782 kb
  • ePUB format
    1749 kb
  • DJVU format
    1885 kb
  • Rating:
    4.2
  • Votes:
    572
  • Formats:
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Neural Networks book. Goodreads helps you keep track of books you want to read. Start by marking Neural Networks: Advances And Applications as Want to Read: Want to Read savin. ant to Read.

Neural Networks book.

Neural networks : advances and applications. Amsterdam ; New York : New York : North-Holland ; Distributed for the . and Canada, Elsevier Science Pub. Co. MLA Citation. Co Amsterdam ; New York : New York 1991. Australian/Harvard Citation.

The present volume is a natural follow-up to Neural Networks: Advances and Applications which appeared one year .

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 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.

Rubrics: Neural networks (Computer science).

by Erol Gelenbe Ecole des Hautes Etudes en Informatique, Université René Descartes (Paris V) 45 rue des Saints-Pères 75006 Paris, France erol. fr, Tel: 33 1 42862231 Fax: 33 1 42862232 Abstract The capacity to learn from examples is one of the most desirable features of neural network models. We present a learning algorithm for the recurrent random network model (Gelenbe 89,90) using gradient descent of a quadratic error function. Start by marking Neural Networks: Advances and Applications, 2 as Want to Read: Want to Read savin.

Artificial neural networks may probably be the single most successful technology in the last two decades . The purpose of this book is to provide recent advances of artificial neural networks in biomedical applications.

Artificial neural networks may probably be the single most successful technology in the last two decades which has been widely used in a large variety of applications in various areas. The book begins with fundamentals of artificial neural networks, which cover an introduction, design, and optimization. Advanced architectures for biomedical applications, which offer improved performance and desirable properties, follow.

Neural networks represent a new generation of information processing paradigms designed to mimic-in a very limited .

Neural networks represent a new generation of information processing paradigms designed to mimic-in a very limited sense-the human brain.

APPLICATIONS OF NEURAL NETWORKS Evolu Evolution of Neural Networks for Control of Pursuit & Evasion: I INTRODUCTION TO ARTIFICIAL INTELLIGENCE Artificial Intelligence is a combination of computer science, physiology, and philosophy. Artificial Intelligence (AI) is the area of computer science focusing on creating machines that can engage on behaviors that humans consider intelligent.

Nevertheless, it seems that the applications of CVNNs and hypercomplex-valued neural networks are very promising. Do you want to read the rest of this article? Request full-text. Citations (1). References (3).

It is expected that Neural Networks will find their niche among the methods and techniques that computer scientists use for intrinsically difficult problems. An attraction of Neural Networks is the dialogue established between computer science, biology, physics, psychology, numerical and non-linear analysis, and other areas. In the future, it may be discovered that Neural Networks are useful for the computationally fast and approximate solution of certain decision problems which are based on simultaneously acting diverse criteria with information of different forms. This book is a snapshot of academic and industrial research in Neural Network theory and of its major applications, written by active contributors to the field, including computer scientists, electrical engineers and physicists.