klt-dct

这是一个自己写的关于fft变换的快速源程序，可以达到很高的性能。(This is an fft transform himself wrote about the rapid source, you can achieve high performance.)

霍夫曼编码程序 对给定的概率 生成霍夫曼编码 希望大家给点意见(Huffman encoding procedure to generate the probability of a given Huffman code to the point I hope everyone)

哈夫曼编码译码系统，设置发送者和接受者两个功能， 发送者的功能包括： ①输入待传送的字符信息； ②统计字符信息中出现的字符种类数和各字符出现的次数（频率）； ②根据字符的种类数和各自出现的次数建立哈夫曼树； ③利用以上哈夫曼树求出各字符的哈夫曼编码； ④将字符信息转换成对应的编码信息进行传送。 接受者的功能包括： ①接收发送者传送来的编码信息； ②利用上述哈夫曼树对编码信息进行翻译，即将编码信息还原成发送前的字符信息。 (Huffman decoding system, set the sender and the recipient of two functions, the sender' s features include: (1) input to be transmitted character information ② statistical character information, the number of types of characters and characters the number of occurrences (frequency create a Huffman tree) ② According to the number of types of characters and their respective number of occurrences ③ use the Huffman tree to find the characters Huffman coding ④ character information into the corresponding coding information for delivery. The recipient of the features include: (1) to receive the coded information to the sender transmission ② above Huffman tree coded information to be translated, is about to coded information to restore the character information before sending.)

ezw程序，主要对图像进行小波变换，然后基于ezw算法进行编码(EZW process, mainly on the image wavelet transform, and then based on the EZW coding algorithm)

视频的源代码，初学者可以参考，很有启发的。祝大家学c#快提高(Video of the source code, can refer to for beginners, very inspired. I wish you all learn c# Soon improve)

说明：  基于ANN神经网络预测方法，可以较为精确地绘制出预测值与实际值以及误差的曲线(ANN-based neural network prediction method, you can more accurately draw predictive value and the actual value and the error curve)

this is renderer function

罚函数法matlab程序.希望对大家有用.(Matlab program SUMT. Wishes to all useful.)

CONTOURLET去噪。添加了高斯噪声很好的实现了图像的多尺度分解下的去噪与重建。实现了多尺度分解的子带去噪。(CONTOURLET denoise .this is denoise program. my english is poor!)

求解线性矩阵不等式简单方便--与LMI工具箱相比(Solving linear matrix inequalities is simple and convenient- as compared with the LMI toolbox)