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Record Nr. |
UNINA9910823618203321 |
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Autore |
Kuzʹmina M. G (Margarita Georgievna) |
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Titolo |
Oscillatory neural networks : in problems of parallel information processing / / Margarita G. Kuzmina, Eduard A. Manykin, Evgeny Grichuk |
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Pubbl/distr/stampa |
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Berlin ; ; Boston : , : Walter de Gruyter GmbH & Co. KG, , [2014] |
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©2014 |
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ISBN |
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Descrizione fisica |
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1 online resource (172 p.) |
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Altri autori (Persone) |
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ManykinEduard |
GrichukEvgeny |
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Disciplina |
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Soggetti |
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Human information processing |
Neural networks (Neurobiology) |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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Description based upon print version of record. |
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Nota di bibliografia |
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Includes bibliographical references and index. |
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Nota di contenuto |
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Frontmatter -- Preface -- Acknowledgments -- Contents -- 1. Introduction -- 2. Neural and oscillatory networks of associative memory -- 3. Oscillatory networks for modeling the brain structures performance -- 4. Image processing based on the oscillatory network model -- 5. Parallel information processing and photon echo -- 6. Stochastic oscillators for modeling polarized light beams -- Summary and some perspectives -- Index |
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Sommario/riassunto |
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Understanding of the human brain functioning currently represents a challenging problem. In contrast to usual serial computers and complicated hierarchically organized artificial man-made systems, decentralized, parallel and distributed information processing principles are inherent to the brain. Besides adaptation and learning, which play a crucial role in brain functioning, oscillatory neural activity, synchronization and resonance accompany the brain work. Neural-like oscillatory network models, designed by the authors for image processing, allow to elucidate the capabilities of dynamical, synchronization-based types of image processing, presumably exploited by the brain. The oscillatory network models, studied by means of computer modeling and qualitative analysis, are presented |
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and discussed in the book. Some other problems of parallel distributed information processing are also considered, such as a recall process from network memory for large-scale recurrent associative memory neural networks, performance of oscillatory networks of associative memory, dynamical oscillatory network methods of image processing with synchronization-based performance, optical parallel information processing based on the nonlinear optical phenomenon of photon echo, and modeling random electric fields of quasi-monochromatic polarized light beams using systems of superposed stochastic oscillators. This makes the book highly interesting to researchers dealing with various aspects of parallel information processing. |
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