Pattern recognition using neural networks theory and algorithms for engineers and scientists
Pattern Recognition Using Neural Networks covers traditional linear pattern recognition and its nonlinear extension via neural networks. The approach is algorithmic for easy implementation on a computer, which makes this a refreshing what-why-and-how text that contrasts with the theoretical approach...
Сохранить в:
| Главный автор: | |
|---|---|
| Язык: | Undetermined English |
| Опубликовано: |
New York
Oxford University Press
1997
|
| Предметы: | |
| Метки: |
Добавить метку
Нет меток, Требуется 1-ая метка записи!
|
| Thư viện lưu trữ: | Trung tâm Học liệu Trường Đại học Trà Vinh |
|---|
| Итог: | Pattern Recognition Using Neural Networks covers traditional linear pattern recognition and its nonlinear extension via neural networks. The approach is algorithmic for easy implementation on a computer, which makes this a refreshing what-why-and-how text that contrasts with the theoretical approach and pie-in-the-sky hyperbole of many books on neural networks. It covers the standard decision-theoretic pattern recognition of clustering via minimum distance, graphical and structural methods, and Bayesian discrimination |
|---|---|
| Объем: | xix, 458 p. ill. 25 cm |
| ISBN: | 195079205 |