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this is the DCT image compression code i have tried . i missed out 2 files while uploadin last time sorry :) hey guys i missed 2 files

基于遗传算法的BP神经网络优化算法Matlab实现(Optimization algorithm based on genetic algorithm BP neural network)

This is a simple program to calculate the output of artificial neural network (ANN) using microcontroller ATMega 32. Assume that the neural architecture is : 2 hidden layers with 4 and 2 neurons respectively and 1 layer output with 1 neuron.This program explains the step how to compute the ANN in off-line mode.Means the weights and biases are already exist (microcontroller is not doing the learning steps). These parameters are produced using MATLAB. Therefore, we have already made the appropriate architecture using MATLAB. The tansig function is use in both of hidden layer. Finally, the neural output will be displayed on LCD port C.

从别人那里转载！从别人那里转载 从别人那里转载 (reproduced from others there! Reprinted from others where there is reproduced from others from others where there is reproduced from others reprinted)

This file contains matlab simulation for vector control for induction machine.

基于bp网络的最大误差逆向传播算法的实现(Maximum error back- propagation algorithm implementation based on BP network)

考虑由于多普勒原因引起的衰落对在离散多径信道上传输的QPSK信号的影响(Consider the causes of the decline due to Doppler discrete multipath channel in the transmission of QPSK signals)

该算法是实现交叉分析表分析。包含卡方检验，似然比检验，交叉分析表，方向度量，对称度量。(The algorithm is to achieve cross-analysis table analysis. Contains the chi-square test, likelihood ratio test, cross analysis table, measure direction, symmetric metric.)

有用的几个动力学物理量。包括自相关函数(acorr.m)，复杂度(complexity.m)，最近邻点(fnn.m)，局部非线性预测误差(nlpe.m，Shannon复杂度（Shannon.m）,嵌入窗估计(window.m)(Several dynamic invariants and measures that may be useful. Included are algorithms for autocorrelation (acorr.m), complexity (complexity.m), false nearest neighbours (fnn.m), local nonlinear prediction error (nlpe.m), Shannon complexity (shannon.m) and the embedding window estimator (window.m). )

在matlab画图时 能增加两条数据指针 方便读取数据(put data cursors on your plots)