资源列表
DFNN
- 动态模糊神经网络，做MG 数据的测试，已经调通，可靠运行，效果不错-Dynamic neural network, do MG test data has been transferred through the reliable operation, good results
XWY_BP_net
- 这是一个用遗传算法对神经网络模型进行寻优，得到最优的输入和输出的程序，类似于对非线性函数极值寻优。-This is a neural network model optimization using genetic algorithm, the optimal input and output procedures, similar to Extreme nonlinear function optimization.
wendang
- 这是一个讲述如何将训练好的神经网络的数学表达式提取出来的word文档，文档里面有实际的例子，供大家参考。-This is a mathematical expression that describes how the trained neural network extracted the word document, the document there are practical examples for your reference.
PSOmatlabdaima
- 这是一个关于PSO算法介绍的PDF文档，文档里面阐述了PSO的原理，以及改进的PSO，包含有相关的程序，可以根据自己的实际情况修改目标函数，从而满足自己的寻优要求。-This is a PSO algorithm describes the PDF document, the document which describes the principle of the PSO, and improved PSO, contains the relevant procedures, the obje
maze_TD_lamda
- 时序差分学习算法TD(lamda)求解N*N方格走迷宫问题，求解每个方格的V值-Temporal difference learning algorithm for N*N maze problem
BP
- 三层神经网络算法，不适用MATLAB的库函数，自带数据集，测试通过-Three-layer neural network algorithm, does not apply MATLAB library functions, comes with data sets, tested
svm
- 基于matlab用支持向量机实现分类决策 -Based on matlab support vector machine to classify Decision
fast-rcnn-master
- Fast Region-based Convolutional Networks for object detection. Fast R-CNN** is a fast framework for object detection with deep ConvNets. Fast R-CNN - trains state-of-the-art models, like VGG16, 9x faster than traditional R-CNN and 3x faster than
xm_LeakMax_MainProg
- 多态系统的贝叶斯网络模型的参数学习算法，基于Noisy-Max模型-Parameters Learning of Bayesian Networks for Multistate System，based Noisy-MAX model
xm_LeakMax_MainProg_Alarm
- BN网络建模，Alarm标准案例中的节点参数学习算法，基于Noisy-Max模型-Based Noisy-Max model，Parameters Learning of Bayesian Networks for Alarm Case
xm_LeakMax_MainProg_Hepar
- 基于因果独立模型的Hepar网络参数学习算法，Hepar网络是BN学习中常用的标准案例-Parameters Learning of Bayesian Networks Based on Independence of Causal Influence Model for Hepar Case
xm_CPTDistanceCompare
- BN网络参数之间的KL距离 (Kullback–Leibler Distance) 计算，用于比较相似度-BN KL distance between network parameters calculation, used to compare similarity