搜索资源列表
bp
- 神经网络数据辨识，10个节点的数据加入模糊数据处理-Neural network data to identify, 10-node data by adding fuzzy data processing
dyl1
- 利用支持向量机对T-S型模糊系统建模的方法，结合BP算法对参数进行优化，从一定程度上解决模糊系统建模所存在的模型结构复杂、维数灾、泛化能力不强和实时性差等问题。-this paper analyzed the approach that applied support vector machines to create novel model in the T-S fuzzy system, combined with BP algorithm which could optimize it,
BP_FUZZY
- 用BP神经网络优化模糊控制器，进行学习，系统有两个输入，输出误差曲线和期望曲线，BP学习误差曲线-BP neural network to optimize the fuzzy controller learning system has two inputs, the output error curve and expectations of the curve, the BP learning error curve
fpids
- 基于模糊控制的BP神经网络PID控制器，规则简单，变通性强，学习时间简短。-Fuzzy Control Based on BP neural network PID controller, the rule is simple, flexible and strong, short learning time.
BP-recognize
- 神经网络学习相关：基于BP网络实现模糊字母识别 设计一个标准BP学习算法训练网络，实现对加噪字母的识别 -Neural network learning relevant: fuzzy identification letters design a standard BP learning algorithm to train the network based on BP network, adding noise to achieve recognition of the lette
基于BP神经网络的模糊控制算法程序
- 通过BP神经网络对模糊规则的学习能跟好的控制，实现模糊PID的有效控制。(Through learning fuzzy rules by BP neural network, better control effect can be achieved.)