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| 003 | MX-SnUAN | ||
| 005 | 20160429154924.0 | ||
| 007 | cr nn 008mamaa | ||
| 008 | 150903s2006 xxk| o |||| 0|eng d | ||
| 020 |
_a9781846283031 _99781846283031 |
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| 024 | 7 |
_a10.1007/1846283035 _2doi |
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| 035 | _avtls000343795 | ||
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_a201509030750 _bVLOAD _c201404121005 _dVLOAD _c201404090743 _dVLOAD _y201402061205 _zstaff |
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_aMX-SnUAN _bspa _cMX-SnUAN _erda |
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| 050 | 4 | _aQ342 | |
| 100 | 1 |
_aDu, K. -L. _eautor _9323377 |
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| 245 | 1 | 0 |
_aNeural Networks in a Softcomputing Framework / _cby K. -L. Du, M. N. S. Swamy. |
| 264 | 1 |
_aLondon : _bSpringer London, _c2006. |
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| 300 |
_aL, 566 páginas 116 ilustraciones _brecurso en línea. |
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| 336 |
_atexto _btxt _2rdacontent |
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| 337 |
_acomputadora _bc _2rdamedia |
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| 338 |
_arecurso en línea _bcr _2rdacarrier |
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| 347 |
_aarchivo de texto _bPDF _2rda |
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| 500 | _aSpringer eBooks | ||
| 505 | 0 | _aFundamentals of Machine Learning and Softcomputing -- Multilayer Perceptrons -- Hopfield Networks and Boltzmann Machines -- Competitive Learning and Clustering -- Radial Basis Function Networks -- Principal Component Analysis Networks -- Fuzzy Logic and Neurofuzzy Systems -- Evolutionary Algorithms and Evolving Neural Networks -- Discussion and Outlook. | |
| 520 | _aConventional model-based data processing methods are computationally expensive and require experts’ knowledge for the modelling of a system; neural networks provide a model-free, adaptive, parallel-processing solution. Neural Networks in a Softcomputing Framework presents a thorough review of the most popular neural-network methods and their associated techniques. This concise but comprehensive textbook provides a powerful and universal paradigm for information processing. Each chapter provides state-of-the-art descriptions of the important major research results of the respective neural-network methods. A range of relevant computational intelligence topics, such as fuzzy logic and evolutionary algorithms, are introduced. These are powerful tools for neural-network learning. Array signal processing problems are discussed in order to illustrate the applications of each neural-network model. Neural Networks in a Softcomputing Framework is an ideal textbook for graduate students and researchers in this field because in addition to grasping the fundamentals, they can discover the most recent advances in each of the popular models. The systematic survey of each neural-network model and the exhaustive list of references will enable researchers and students to find suitable topics for future research. The important algorithms outlined also make this textbook a valuable reference for scientists and practitioners working in pattern recognition, signal processing, speech and image processing, data analysis and artificial intelligence. | ||
| 590 | _aPara consulta fuera de la UANL se requiere clave de acceso remoto. | ||
| 700 | 1 |
_aSwamy, M. N. S. _eautor _9315670 |
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| 710 | 2 |
_aSpringerLink (Servicio en línea) _9299170 |
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| 776 | 0 | 8 |
_iEdición impresa: _z9781846283024 |
| 856 | 4 | 0 |
_uhttp://remoto.dgb.uanl.mx/login?url=http://dx.doi.org/10.1007/1-84628-303-5 _zConectar a Springer E-Books (Para consulta externa se requiere previa autentificación en Biblioteca Digital UANL) |
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