| 000 | 01001nam a22002177a 4500 | ||
|---|---|---|---|
| 003 | CUTN | ||
| 005 | 20231120171533.0 | ||
| 008 | 231120b |||||||| |||| 00| 0 eng d | ||
| 020 | _a9780000988546 | ||
| 041 | _aEnglish | ||
| 082 |
_223 _a006.31 _bGRA |
||
| 100 | _aGraupe, Daniel | ||
| 245 |
_aDeep learning neural networks : _bDesign and case studies / _cDaniel Graupe |
||
| 260 |
_aSingapore : _bWorld Scientific Publishing, _cr 2022. |
||
| 300 |
_axvi, 263 p.: _bill. ; _c25 cm. |
||
| 505 |
_a1. Deep learning neural networks: methodology and scope
2. Basic concepts of neural networks
3. Back-propagation
4. The cognitron and neocognitron
5. Deep learning convolutional neural networks
_t6. LAMSTAR-1 and LAMSTAR-2 neural networks 7. Other neural networks for deep learning 8. Case studies 9. Concluding comments |
||
| 650 | _aNeural networks (Computer science) Problems, exercises, etc | ||
| 650 | _aProblems and exercises | ||
| 690 | _aComputer Science | ||
| 942 |
_2ddc _cBOOKS |
||
| 999 |
_c40424 _d40424 |
||