| 000 | 03406nam a22006857a 4500 | ||
|---|---|---|---|
| 001 | 8806 | ||
| 003 | OSt | ||
| 005 | 20240325120159.0 | ||
| 008 | 240325m20192020-usa|||| |||| 001 0 eng d | ||
| 020 |
_a9780367656492 _qpaper back |
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| 040 | _cCentral Library, Khulna University | ||
| 041 | _2eng | ||
| 082 |
_a006.32 _bZHT |
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| 100 | _aZhang,Yunong | ||
| 245 |
_a Toward deep neural networks : _bWASD neuronet models, algorithms, and applications/ _cby Yunong Zhang, Dechao Chen , Chengxu Ye |
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| 250 | _a1st ed. | ||
| 260 |
_aBoca Raton: _b Chapman & Hall/CRC, _c 2020 |
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| 300 |
_axxv, 341p.: _bill.; _c26 cm. |
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| 350 | _a3618.00 | ||
| 440 | _a Chapman & Hall/CRC artificial intelligence and robotics series | ||
| 504 | _aIncludes Index, bibliography and glossary | ||
| 505 | 0 |
_a
_tI Single-Input-Single-Output Neuronet |
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| 505 | _a1 Single-Input Euler-Polynomial WASD Neuronet | ||
| 505 | _a2 Single-Input Bernoulli-Polynomial WASD Neuronet | ||
| 505 | _a3 Single-Input Laguerre-Polynomial WASD Neuronet | ||
| 505 | _tII Two-Input-Single-Output Neuronet | ||
| 505 | _a4 Two-Input Legendre-Polynomial WASD Neuronet | ||
| 505 | _a5 Two-Input Chebyshev-Polynomial-of-Class-1WASD Neuronet | ||
| 505 | _a6 Two-Input Chebyshev-Polynomial-of-Class-2 WASD Neuronet | ||
| 505 | _tIII Three-Input-Single-Output Neuronet | ||
| 505 | _a7 Three-Input Euler-Polynomial WASD Neuronet | ||
| 505 | _a8 Three-Input Power-Activation WASD Neuronet | ||
| 505 | _tIV General Multi-Input Neuronet | ||
| 505 | _a 9 Multi-Input Euler-Polynomial WASD Neuronet | ||
| 505 | _a10 Multi-Input Bernoulli-Polynomial WASD Neuronet | ||
| 505 | _a11 Multi-Input Hermite-Polynomial WASD Neuronet | ||
| 505 | _a12 Multi-Input Sine-ActivationWASD Neuronet | ||
| 505 |
_a
_tV Population Applications Using Chebyshev-Activation Neuronet |
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| 505 | _a13 Application to Asian Population Prediction | ||
| 505 | _a14 Application to European Population Prediction | ||
| 505 | _a15 Application to Oceania Population Prediction | ||
| 505 | _a16 Application to Northern American Population Prediction | ||
| 505 | _a17 Application to Indian Subcontinent Population Prediction | ||
| 505 | _a18 Application to World Population Prediction | ||
| 505 | _tVI Population Applications Using Power-Activation Neuronet | ||
| 505 | _a19 Application to Russian Population Prediction | ||
| 505 | _a20 WASD Neuronet versus BP Neuronet Applied to Russia Population Prediction | ||
| 505 | _a21 Application to Chinese Population Prediction | ||
| 505 | _a22 WASD Neuronet versus BP Neuronet Applied to Chinese Population Prediction | ||
| 505 | _tVII Other Applications | ||
| 505 | _a23 Application to USPD Prediction | ||
| 505 | _a24 Application to Time Series Prediction | ||
| 505 | _a25 Application to GFR Estimation | ||
| 520 | _aThis book introduces deep neural networks, with a focus on the weights-and-structure determination (WASD) algorithm. Based on the authors’ 20 years of research experience on neuronets, the book explores the models, algorithms, and applications of the WASD neuronet. | ||
| 650 | _aNeural networks (Computer science) | ||
| 650 |
_aBusiness and Economics _xStatistics |
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| 700 | _aChen,Dechao | ||
| 700 | _aYe, Chengxu | ||
| 942 |
_2ddc _n0 _cBK |
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| 999 |
_c8806 _d8806 |
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