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احتاج معلومات عن الneural network

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    احتاج معلومات عن الneural network


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  2. #2
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    Handbook of Neural Network Signal Processing
    ISBN: 0849323592
    Author: Yu Hen Hu
    Publisher: CRC Press
    Edition: 1st edition

    (September 21, 2001)
    Hardcover: 408 pages


    Summary:
    The use of neural networks is permeating every area of signal processing. They can provide powerful means for solving many problems, especially in nonlinear, real-time, adaptive, and blind signal processing.
    "The Handbook of Neural Network Signal Processing" brings together applications that were previously scattered among various publications to provide an up-to-date, detailed treatment of the subject from an engineering point of view.The authors cover basic principles, modeling, algorithms, architectures, implementation procedures, and well-designed simulation examples of audio, video, speech, communication, geophysical, sonar, radar, medical, and many other signals.
    The subject of neural networks and their application to signal processing is constantly improving. You need a handy reference that will inform you of current applications in this new area. "The Handbook of Neural Network Signal Processing" provides this much needed service for all engineers and scientists in the field.

    Book Info
    Brings together applications that were previously scattered among various publications to provide and up to date, detailed treatment of the subject from an engineering point of view.


    http://rapidshare.de/files/20590134/...DWARF.zip.html
    أو
    http://www.ru.lv/~peter/zinatne/eboo...Processing.pdf
    أو
    http://rapidshare.de/files/7972016/C...ssing.pdf.html
    أو
    http://djvu.504.com1.ru:8019/WWW/373...626aacd81c.pdf



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    Understanding Product Design for Injection Molding-665566551-jpg 665566551-jpg

    { الَّذِينَ آتَيْنَاهُمُ الْكِتَابَ يَعْرِفُونَهُ كَمَا يَعْرِفُونَ أَبْنَاءَهُمُ }

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    Book Description
    Neural networks represent a new generation of information processing paradigms designed to mimic-in a very limited sense-the human brain. They can learn, recall, and generalize from training data, and with their potential applications limited only by the imaginations of scientists and engineers, they are commanding tremendous popularity and research interest. Over the last four decades, researchers have reported a number of neural network paradigms, however, the newest of these have not appeared in book form-until now. Recent Advances in Artificial Neural Networks collects the latest neural network paradigms and reports on their promising new applications. World-renowned experts discuss the use of neural networks in pattern recognition, color induction, classification, cluster detection, and more. Application engineers, scientists, and research students from all disciplines with an interest in considering neural networks for solving real-world problems will find this collection useful


    http://rapidshare.de/files/20752275/...DWARF.zip.html



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    { الَّذِينَ آتَيْنَاهُمُ الْكِتَابَ يَعْرِفُونَهُ كَمَا يَعْرِفُونَ أَبْنَاءَهُمُ }

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    Neural Network Modeling
    Statistical Mechanics and Cybernetic Perspectives

    ISBN: 0849324882
    Author: Perambur S. Neelakanta / Dolores F. De Groff
    Publisher: CRC Press
    Edition: (July 12, 1994)
    Pages: 256 pages
    URL: http://www.amazon.com/exec/obidos/re...N%2F0849324882
    Summary:
    Neural Network Modeling offers a cohesive approach to the statistical mechanics and principles of cybernetics as a basis for neural network modeling. It brings together neurobiologists and the engineers who design intelligent automata to understand the physics of collective behavior pertinent to neural elements and the self-control aspects of neurocybernetics. The theoretical perspectives and explanatory projections portray the most current information in the field, some of which counters certain conventional concepts in the visualization of neuronal interactions


    http://www.ru.lv/~peter/zinatne/eboo...k_Modeling.pdf
    أو
    http://tinyurl.com/8lqrf



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    { الَّذِينَ آتَيْنَاهُمُ الْكِتَابَ يَعْرِفُونَهُ كَمَا يَعْرِفُونَ أَبْنَاءَهُمُ }

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    Kalman Filtering and Neural Networks

    Author: Simon Haykin
    Publisher: Wiley-Interscience
    URL: /http://www.amazon.com/exec/obidos/redirect?tag=songstech-20&path=ASIN%2F0471369985
    Summary:
    State-of-the-art coverage of Kalman filter methods for the design of neural networks
    This self-contained book consists of seven chapters by expert contributors that discuss Kalman filtering as applied to the training and use of neural networks. Although the traditional approach to the subject is almost always linear, this book recognizes and deals with the fact that real problems are most often nonlinear.
    The first chapter offers an introductory treatment of Kalman filters with an emphasis on basic Kalman filter theory, Rauch-Tung-Striebel smoother, and the extended Kalman filter. Other chapters cover:
    * An algorithm for the training of feedforward and recurrent multilayered perceptrons, based on the decoupled extended Kalman filter (DEKF)
    * Applications of the DEKF learning algorithm to the study of image sequences and the dynamic reconstruction of chaotic processes
    * The dual estimation problem
    * Stochastic nonlinear dynamics: the expectation-maximization (EM) algorithm and the extended Kalman smoothing (EKS) algorithm
    * The unscented Kalman filter
    Each chapter, with the exception of the introduction, includes illustrative applications of the learning algorithms described here, some of which involve the use of simulated and real-life data. Kalman Filtering and Neural Networks serves as an expert resource for researchers in neural networks and nonlinear dynamical systems


    http://rapidshare.de/files/19795009/...l_Networks.pdf

    أو
    http://rapidshare.de/files/4448886/SHaykin.rar.html



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    { الَّذِينَ آتَيْنَاهُمُ الْكِتَابَ يَعْرِفُونَهُ كَمَا يَعْرِفُونَ أَبْنَاءَهُمُ }

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    Author: Larry Medsker
    Publisher: CRC Press

    Summary:
    With existent uses ranging from motion detection to music synthesis to financial forecasting, recurrent neural networks have generated widespread attention. The tremendous interest in these networks drives Recurrent Neural Networks: Design and Applications, a summary of the design, applications, current research, and challenges of this subfield of artificial neural networks.This overview incorporates every aspect of recurrent neural networks. It outlines the wide variety of complex learning techniques and associated research projects. Each chapter addresses architectures, from fully connected to partially connected, including recurrent multilayer feedforward. It presents problems involving trajectories, control systems, and robotics, as well as RNN use in chaotic systems. The authors also share their expert knowledge of ideas for alternate designs and advances in theoretical aspects.The dynamical behavior of recurrent neural networks is useful for solving problems in science, engineering, and business. This approach will yield huge advances in the coming years. Recurrent Neural Networks illuminates the opportunities and provides you with a broad view of the current events in this rich field.


    http://rapidshare.de/files/20752410/...DWARF.zip.html
    أو
    http://www.ebooksclub.org/?link=H142qC



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    التعديل الأخير تم بواسطة أهل الحديث ; 2006-09-02 الساعة 02:27 AM
    Understanding Product Design for Injection Molding-665566551-jpg 665566551-jpg

    { الَّذِينَ آتَيْنَاهُمُ الْكِتَابَ يَعْرِفُونَهُ كَمَا يَعْرِفُونَ أَبْنَاءَهُمُ }

  7. #7
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    Neural Networks for Instrumentation, Measurement and Related Industrial Applications
    (Nato-Computer and Systems Sciences, 185)

    Author: NATO ADVANCED STUDY INSTITUTE ON NEURAL
    Publisher: Ios Pr Inc
    Publication Date: 2003-01

    http://rapidshare.de/files/4158441/SAblameyko.rar.html
    Password: www.AvaxHome.ru


    وان احتجت أى شئ أخر ابلغنى لمساعدتك
    الله يوفقك أخى


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    { الَّذِينَ آتَيْنَاهُمُ الْكِتَابَ يَعْرِفُونَهُ كَمَا يَعْرِفُونَ أَبْنَاءَهُمُ }

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  9. #9
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    اخي العزيز ( محب الله ورسوله ) ......

    ماشاء الله ....ماشاء الله .... ماشاء الله عليك ...

    كفيت و وفيت ....

    والله تستاهل عضو اكثر من مميز .....

    جزاك الله خير .... الله يوفقك....


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