搜索资源列表
XorNN
- 编了一个用C++程序实现BP网络的异或问题。-compiled a C program BP network problems or differences.
BPNeuralNetwork2
- BP神经网络解决异或问题,用VC可以打开浏览!也可与MATLAB接口使用.-BP neural network solutions differences or problems, with VC can open here! Also with the use of MATLAB interface.
BPClassification
- 本程序用bp解决广义异或问题并提供了对输入样本的改进。-bp to solve the problem and the generalized XOR improve the input samples.
bpxor
- 利用BP网络实现异或功能，对输入矢量进行分类，源程序-BP networks using XOR function to classify the input vector, source code
main
- BP算法的批处理，并且实现“异或”功能。-BP algorithm
IrisClassification
- Iris数据集的分类程序，包括线性分类器实验，BP网络分类器实验，以及异或数据的BP网络分类实验，外带试验报告-Iris data set of classification procedures, including linear classification experiment, BP network classifier experiments, and different BP networks or data classification experiment, take-test
bp
- 使用BP算法实现异或功能，由matlab编程实现，可正确运行。-BP algorithm using the XOR function, the matlab programming, can be run correctly.
BPXOR
- 模式识别作业-自编的BP神经网络判断异或的matlab源代码，每一步都有详细说明。并有详细的结果输出。-Pattern recognition operations- the BP neural network to determine self XOR the matlab source code, detailed descr iption of each step. And a detailed results output.
BP
- BP神经网络异或问题 使用说明：打开文件夹中的BP.m文件，在matlab中运行此m文件，即可在command window中得出结果。压缩包内附说明文件-XOR problem of the BP neural network for use: Open the folder in BP.m file, run this m file in matlab to the outcome of the command window. Compression package containing t
code
- 三道题，包括1：用多层感知器（MLP）神经网络误差反向传播（BP）算法实现异或问题:2：用奇阶互补法设计两带滤波器组(高、低通互补)，进而实现四带滤波器组 3：估计其功率谱-Three questions, including: 1 using multilayer perceptron ( MLP ) neural network and error back propagation ( BP ) algorithm to realize the XOR problem: 2: the odd
ge_bp_xor
- 利用遗传算法解决BP网络异或问题/XOR的分类，-Genetic algorithm to solve the BP network the XOR problem
matlab_1
- 基于C语言编写的为实现两层BP神经网络（一隐层，一输出层）可学习异或映射系统，并且不用神经网络工具箱。-Based on C，without pre-packaged toolbox， to implement 2-layer （one hidden， one output） BP system to be trained to learn function.
matlab-bp
- 本源码用Matlab去解决神经网络中的利用Sigmoid函数去训练的经典异或问题-The classic source Matlab to solve with the use of neural networks to train the Sigmoid function XOR problem
li1
- 请用多层感知器（MLP）神经网络误差反向传播（BP）算法实现异或问题（输入为，要求可以判别输出为0或1），并画出学习曲线。其中，非线性函数采用S型Logistic函数。-Please use the Multilayer Perceptron (MLP) back propagation neural network (BP) algorithm XOR problem (input is required to determine the output is 0 or 1), and draw