一般神经网络用于信号处理的经典教科书,The field of artificial neural networks has made tremendous progress in the past 20 years in terms of theory, algorithms, and applications. Notably, the majority of real world neural network appli- cations have involved the solution of difficult statistical signal processing problems. Compared to conventional signal processing algorithms that are mainly based on linear models, artificial neural networks offer an attractive alternative by providing nonlinear parametric models with universal approximation power, as well as adaptive training algorithms. The availability of such powerful modeling tools motivated numerous research efforts to explore new signal processing applications of artificial neural networks. During the course of the research,many neural network paradigmswere proposed. Some of them are merely reincarnations of existing algorithms formulated in a neural network-like setting, while the others provide new perspectives toward solving nonlinear adaptive signal processing. More importantly, there are a number of emergent neural network paradigms that have found successful real world applications.
- lican7668890212011-11-08一般般,讲的太深奥了,不适合初学者
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