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Titlebook: New Soft Computing Techniques for System Modeling, Pattern Classification and Image Processing; Leszek Rutkowski Book 2004 Springer-Verlag

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書目名稱New Soft Computing Techniques for System Modeling, Pattern Classification and Image Processing
編輯Leszek Rutkowski
視頻videohttp://file.papertrans.cn/666/665756/665756.mp4
概述New Soft Computing Techniques for System Modeling, Pattern Classification, Image Processing.Written by a pioneer in the field of human-friendly technology.Includes supplementary material:
叢書名稱Studies in Fuzziness and Soft Computing
圖書封面Titlebook: New Soft Computing Techniques for System Modeling, Pattern Classification and Image Processing;  Leszek Rutkowski Book 2004 Springer-Verlag
描述Science has made great progress in the twentieth century, with the establishment of proper disciplines in the fields of physics, computer science, molecular biology, and many others. At the same time, there have also emerged many engineering ideas that are interdisciplinary in nature, beyond the realm of such orthodox disciplines. These in- clude, for example, artificial intelligence, fuzzy logic, artificial neural networks, evolutional computation, data mining, and so on. In or- der to generate new technology that is truly human-friendly in the twenty-first century, integration of various methods beyond specific disciplines is required. Soft computing is a key concept for the creation of such human- friendly technology in our modern information society. Professor Rutkowski is a pioneer in this field, having devoted himself for many years to publishing a large variety of original work. The present vol- ume, based mostly on his own work, is a milestone in the devel- opment of soft computing, integrating various disciplines from the fields of information science and engineering. The book consists of three parts, the first of which is devoted to probabilistic neural net- works. Neural
出版日期Book 2004
關(guān)鍵詞Hardware; Pattern Classification; Probabilistic Neural Networks; Recursive Least Square Methods; Regress
版次1
doihttps://doi.org/10.1007/978-3-540-40046-2
isbn_softcover978-3-642-05820-2
isbn_ebook978-3-540-40046-2Series ISSN 1434-9922 Series E-ISSN 1860-0808
issn_series 1434-9922
copyrightSpringer-Verlag Berlin Heidelberg 2004
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Introduction to Probabilistic Neural NetworksIn the fifties and sixties problems of statistical pattern classification in the stationary case were accomplished by means of parametric methods, using the available apparatus of statistical mathematics (e.g. [35], [75], [89], [90], [293]). The knowledge of the probability density to an accuracy of
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he need for monitoring to identify potential performance failures and ensure efficient operation. The essential importance of communication and information in these processes has been emphasized, and the IT (information technology) utilized in these operations has been reviewed..The objective of a d
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