资源列表
bp_train_VC
- BP的训练方法.删除init_wj_hid_output与init_wj_input_hid可以进行新的学习!不然只是按老方式学习!这是一个最简单的BP算法异或问题!没有阈值，学习速度不可改变!下次会改进!如果同或只需改变输入的方式就可以!-BP's training methods. Delete init_wj_hid_output with init_wj _input_hid can conduct new learning! Otherwise, only the old wa
HopfieldNN0-9Recognise
- This code in this directory implements the binary hopfield network. Source code may be found in HOPNET.CPP. A sample training file is H7x8N4.trn. Sample test pattern files are: H7x8D4.TST, H5x8D7.TST, H5x8D7.TST and H5x8D9.TST, Output of the pr
Kmeans_VC
- 鼎鼎大名的Kmeans的VC实现。广泛用于神经网络、模式识别领域。-the Kmeans the famous VC. Widely used in neural networks, pattern recognition.
BAM_VC
- BAM网络即双向联想记忆网络，是一种可以记忆模式对的两层非线性反馈神经网络。-BAM network is a two-way associative memory networks, it is a memory of the two-mode nonlinear feedback neural network.
CPN_VC
- CPN网络，即对向传播网络，是将Kohonen特征映射网络与Grossberg基本竞争网络相结合，发挥各自特长的一种新型特征映射网络。-CPN network, the right to communication networks, Kohonen feature is the mapping of network and basic Grossberg competing networks combined play to their strong points of a new featu
boltzman_VC
- Boltzmannn机网络是Hinton等人在1985年将模拟退火算法引入到神经网络中，提出的，简称BM网络。-Boltzmannn computer network is Hinton and others in 1985 will be simulated annealing primer access to the neural network, the network referred to BM.
obstacles
- 一种机器人路径规划的matlab程序，可以参考！希望能对大家有所帮助-a robot path planning Matlab procedures, they can refer to. The hope is to help everyone
tsp(c)
- 简单模拟退火算法-货郎担问题.txt（c语言）-simple simulated annealing-traveling salesman problem. Txt (c language)
colocation
- 数据挖掘算法中空间同位规则挖掘的matlab源码-data mining algorithm with space - Rules Mining Matlab FOSS
lw6
- 本人上传的是FP-GROWTH算法的数据挖掘中的关联规则与序列模式-I upload the FP-GROWTH algorithm Data Mining Association Rules and sequence mode
E_M_matlab
- 机器学习中的E M算法，本代码是基于高斯混合模型的E M 算法聚类。-machine learning algorithm E M, the code is based on the Gaussian mixture model clustering algorithm E. M.
OLDA
- 正交线性判别分析（Orthogonal Linear Discriminant Analysis），可以用于数据降维上面。-orthogonal linear discriminant analysis (Orthogonal Linear Discriminan t Analysis), can be used for cutting down the data above.