000 | 03845nam a22006015i 4500 | ||
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001 | 978-3-031-75705-1 | ||
003 | DE-He213 | ||
005 | 20250516160208.0 | ||
007 | cr nn 008mamaa | ||
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050 | 4 | _aQH324.2-.25 | |
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_aMallot, Hanspeter A. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut |
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245 | 1 | 0 |
_aComputational Neuroscience _h[electronic resource] : _bAn Essential Guide to Membrane Potentials, Receptive Fields, and Neural Networks / _cby Hanspeter A. Mallot. |
250 | _a2nd ed. 2024. | ||
264 | 1 |
_aCham : _bSpringer Nature Switzerland : _bImprint: Springer, _c2024. |
|
300 |
_aXIII, 280 p. 109 illus., 74 illus. in color. _bonline resource. |
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336 |
_atext _btxt _2rdacontent |
||
337 |
_acomputer _bc _2rdamedia |
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338 |
_aonline resource _bcr _2rdacarrier |
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347 |
_atext file _bPDF _2rda |
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505 | 0 | _aChapter 1. Excitable Membranes and Neural Conduction -- Chapter 2. Receptive Fields and the Specificity of Neuronal Firing -- Chapter 3. Functional Models of Receptive Fields -- Chapter 4. Fourier Analysis for Neuroscientists -- Chapter 5. Artificial Neural Networks and Classification -- Chapter 6. Artificial Neural Networks With Interacting Output Units -- Chapter 7. Coding and Representation. | |
520 | _aThis book provides an essential introduction to modeling the nervous system at various levels. Readers will learn about the intricate mechanisms of neural activity, receptive fields, neural networks, and information coding. The chapters cover topics such as membrane potentials, the Hodgkin-Huxley theory, receptive fields and their specificity for important stimulus dimensions, Fourier analysis for neuroscientists, pattern recognition and self-organization in neural networks, and the structure of neural representations. The second edition includes revised text and figures for improved readability and completeness. Key points are highlighted throughout to help readers keep track of central ideas. Researchers in the field of neuroscience with backgrounds in biology, psychology, or medicine will find this book particularly beneficial. It is also an invaluable reference for all neuroscientists who use computational methods in their daily work. Whether you are a theoretical scientist approaching the field or an experienced practitioner seeking to deepen your understanding, "Computational Neuroscience - An Essential Guide to Membrane Potentials, Receptive Fields, and Neural Networks" offers a comprehensive guide to mastering the fundamentals of this dynamic discipline. . | ||
541 |
_fUABC ; _cPerpetuidad |
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650 | 0 | _aComputational neuroscience. | |
650 | 0 | _aComputational intelligence. | |
650 | 0 | _aNeurosciences. | |
650 | 0 | _aNeural networks (Neurobiology). | |
650 | 0 | _aNeural circuitry. | |
650 | 1 | 4 | _aComputational Neuroscience. |
650 | 2 | 4 | _aComputational Intelligence. |
650 | 2 | 4 | _aNeuroscience. |
650 | 2 | 4 | _aSystems Neuroscience. |
650 | 2 | 4 | _aNeural Circuits. |
710 | 2 | _aSpringerLink (Online service) | |
773 | 0 | _tSpringer Nature eBook | |
776 | 0 | 8 |
_iPrinted edition: _z9783031757044 |
776 | 0 | 8 |
_iPrinted edition: _z9783031757068 |
776 | 0 | 8 |
_iPrinted edition: _z9783031757075 |
856 | 4 | 0 |
_zLibro electrónico _uhttp://libcon.rec.uabc.mx:2048/login?url=https://doi.org/10.1007/978-3-031-75705-1 |
912 | _aZDB-2-SBL | ||
912 | _aZDB-2-SXB | ||
942 | _cLIBRO_ELEC | ||
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