MATLAB神经网络43个案例分析
说明： 本书共有43章，内容涵盖常见的神经网络（BP、RBF、SOM、Hopfield、Elman、LVQ、Kohonen、GRNN、NARX等）以及相关智能算法（SVM、决策树、随机森林、极限学习机等）。同时，部分章节也涉及了常见的优化算法（遗传算法、蚁群算法等）与神经网络的结合问题。此外，本书还介绍了MATLAB R2012b中神经网络工具箱的新增功能与特性，如神经网络并行计算、定制神经网络、神经网络高效编程等(This book consists of 43 chapters, covering common neural networks (BP, RBF, SOM, Hopfield, Elman, LVQ, Kohonen, GRNN, NARX, etc.) and related intelligent algorithms (SVM, decision tree, random forest, extreme learning machine, etc.). At the same time, some chapters also involve the combination of common optimization algorithms (genetic algorithm, ant colony algorithm, etc.) and neural networks. In addition, the book also introduces the new functions and characteristics of the neural network toolbox in MATLAB R2012b, such as parallel computing of neural networks, customized neural networks, efficient programming of neural networks, etc)
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