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Author(s): | Anthony N. Michel | |||
Collection: | Pure and Applied Mathematics | |||
Publisher: | CRC Press | |||
Year: | 2002 | |||
Language: | English | |||
Pages: | 504 pages | |||
Size: | 2.94 MB | |||
Extension: | ||||
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[content title="Description"]In the present book we concern ourselves exclusively with the qualitative analysis and synthesis of recurrent artificial neural networks. There is an abundance of papers, monographs, and books that address qualitative properties of such networks. However, whereas in these works, the analysis of the networks is frequently incidental to the achievement of some other principal goal, in the present book the network itself is the primary object of inquiry. Works in which the primary object of study is the recurrent neural network itself are rare. Consequently, many of the qualitative attributes and limitations of such networks have been ignored and are therefore obscure. [/content]
[content title="Content"] [/content]
[content title="About the author"]Anthony N. Michel grew up in Romania as a member of the Banat Swabian ethnic minority. Prior to emigrating to the United States in 1952, he lived for five years in a displaced persons camp in Austria.
After receiving a bachelor's degree in electrical engineering in 1958 from Marquette University in Milwaukee, Wisconsin, he spent seven years in the aerospace industry. In 1964, he received a master's degree in mathematics and in 1968 a PhD in electrical engineering from Marquette. In 1973 he received a DSc in applied mathematics from the Technical University of Graz, Austria. [/content]
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