Estimation--Control--and-the--Discrete-Kalman-Fil

数据链路层滑动窗口协议的设计与实现源码 信道模型为8000bps 全双工卫星信道，信道传播时延270 毫秒，信道误码率为10-5，信道提供字节流传输服务，网络层分组长度在240~256字节范围。(Sliding window data link layer protocol design and implementation of source-channel model 8000bps full-duplex satellite channel, the channel propagation delay 270 ms, the channel bit error rate of 10-5, the channel provides a byte stream transfer service, network layer packet length in the range of 240 to 256 bytes.)

this file is a matlab program. File name is 2D fast fourier transform.

Matlab中的遗传算法工具箱，内含多个功能函数，方便调用。(Genetic Algorithm in Matlab toolbox containing a number of performance function to facilitate the call.)

一直一因果系统，画出其零极点图和冲击响应波形(Been a causal system, draw the pole-zero diagram and impulse response waveform)

OFDM Simulation Using Matlab 里面附有详细关于OFDM实现的说明，并给出了MATLAB实现代码(OFDM Simulation Using Matlab inside with detailed description on the OFDM realize, and realize given MATLAB code)

这是模拟飞机飞行的不同阶段的轨迹程序，比较全面，可用于捷联和组合导航的数据来源(This is a simulated flight trajectory of the different stages of process, more comprehensive, can be used in strapdown and navigation data sources)

利用matlab实现数字视频处理的图像采集和压缩采样等运算(Digital video processing using matlab image acquisition and compression sampling and operations)

分类聚类Matlab源程序m文件用于数据的分类聚类(Category clustering Matlab source code m file for the classification of the data clustering)

it is cluster2 matlab code

传统的短时谱估计语音增强算法通常假设语音谱分量相互独立，没有考虑语音谱分量间的相关性。针对这 一问题，该文提出一种新的基于多元Laplace分布模型的短时谱估计算法。首先，假设语音的离散余弦变换(DCT) 系数服从多元Laplace分布，以此利用谱分量间的相关性；在此基础上，利用多元随机矢量的高斯尺度混合模型表 示，推导得到语音DCT系数矢量的最小均方误差(MMSE)估计的解析表达式；并进一步推导了基于该分布模型的 语音存在概率，对最小均方误差估计子进行修正。实验结果表明，该算法在抑制背景噪声和减少语音失真等方面优 于传统的语音增强方法。(The spectral components of speech are usually assumed to be independent in traditional short-time spectrum estimation, which is not the case in practice. Tosolve this problem, a new speech enhancement algorithm with multivariate Laplace speech model is proposed in this paper. Firstly, the speech Discrete Cosine Transform (DCT) coefficients are modeled by a multivariate Laplace distribution, so the correlations between speech spectral components can be exploited. And then a Minimum-Mean-Square-Error (MMSE) estimator based on the proposed model is derived using a Gaussian scale mixture representation of random vectors. Furthermore, the speech presence uncertainty with the new model is derived to modify the MMSE estimator. Experimental results show that the developed method has better noise suppression performance and lower speech distortion compared to the traditional speech enhancement method. )