Principle of Bp Neural network

最新推荐文章于 2023-11-18 22:05:15 发布

Edward_Chan

最新推荐文章于 2023-11-18 22:05:15 发布

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分类专栏： Soft Computing 文章标签： network processing algorithm signal domain function

本文链接：https://blog.youkuaiyun.com/edward_chan/article/details/5307625

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本文探讨了神经网络如何作为软计算的一部分，通过模糊理论提供更灵活、鲁棒性强的计算模型，避免精确直接建模，并强调BP神经网络在非线性函数表达方面的优势。

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in signal processing, wavelet is very famous. whereas in bp neural network, they are the same principle. it is the infinite series. the only difference is that bp network is focus on auto-learning whereas warelet is for time domain convert to frequence domain.

in previous article, i have introdue several fuzzy theory and its application. but why neural network is belong to soft computing? in soft computing, the model is more flexible and robust than the normal one. vision of fuzzy theory is to sketch a fuzzy paradigm. but in neural network, is to avoid to sketch improcise directly. it is as same as GA algorithm.

before few days, i read my teammate's thesis, i found that to representation of computing we have a lot of method, such as formular, rules, and algorithm for procedure etc.

so, in capable of bp neural network, it can represent nonlinear function. and I can call it like this sentence: a bp neural network is one of representation of computing which can expresses nonlinear function with imprecise using infinite series.