资源列表
winsvm2.0
- 本软件是 windows系统平台下的支持向量机软件，包括了支持向量机的几种常用类型，可用于分类和回归-This software is under the windows system platform support vector machine software, including support vector machines for some commonly-used type, can be used for classification and regression
bpqianming
- 基于BP神经网络的手写签名识别方法。训练样本，识别签名-Based on BP Neural Network Recognition of handwritten signatures. Training samples to identify the signature
linennet_tt
- 使用自适应线性神经网络进行预测的实例 很有代表性-The use of adaptive linear neural network to predict very representative example of
neuralnetworks_hw_02
- 神经网络ＢＰ算法Ｃ程序，文件中包含训练数据及测试数据。文件中神经网络训练功能为８位奇偶校验功能。-BP neural network algorithm for C programs, files included in the training data and test data. Document the functional neural network training for eight parity function.
SVM
- ＶＣ＋＋实现的SVM的算法实现，应用于机器学习的好方法．-VC to achieve the SVM algorithm, used in a good way of machine learning.
gene_bpnn_xor
- 标准的遗传算法代码，下面是程序：function y=fitness(chrom,p,aim) global P_cross P_mutation [Popsize len]=size(chrom) fitness_gene=zeros(Popsize,1) in_he=zeros(4,1) out_he=zeros(4,1) in_out=0 out_out=0 -Standard genetic algorithm code, the following
yiqun
- 蚁群算法程序，采用C++语言实现蚁群算法程序。-Ant colony algorithm procedure for the C++ Language ant colony algorithm procedures.
Matlabfuzzy
- 本文介绍一种倒立摆系统的软硬件开发，其硬件系统具有低成本、高可靠性和稳定性等优点；其软件系统在Matlab环境下编程和实时控制，源代码完全开放，而且可调用丰富的Matlab工具箱函数，非常适用于教学和科研上的再学习和开发。-This paper introduces an inverted pendulum system software and hardware development, the hardware system has a low-cost, high reliability
qga_image
- 量子遗传算法用于图象处理 量子遗传算法用于图象处理-Quantum Genetic Algorithm for Image Processing Quantum Genetic Algorithm for Image Processing
bp_back
- 本程序为一个误差向后传播的三层前馈神经网络有指导的学习算法。-This procedure for a transmission error backward three feedforward neural network learning algorithm for guidance.
Neuroscience
- 用matlab实现模拟神经元模型，采用Hodkgin-Huxley方程为主要算法-Using matlab for analog neural model, using Hodkgin-Huxley equations as the main algorithm
DT1RBFGJDTDSYJYnet
- 对动态一阶对象采用RBF神经网络进行建模的源程序,经过调试,直接就可以由MATLAB运行!-Dynamic first-order object to the use of RBF neural network to model the source, after debugging, directly from MATLAB can be run!