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说明：  本程序基于MATLAB设计了数字滤波器实现的对含有噪声的文件的过滤(The program is based on MATLAB implementation of a digital filter paper with noise filtering)

介绍了一种用Matlab 信号处理工具箱进行数字滤波器设计的方法。给出了工具箱中的FDATool 图形用户接 口的详细使用方法,用FDATool 进行滤波器设计,可以随时对比设计要求和滤波器特性调整参数,直观简便,在每次改变参 数时,由于计算机的超强运算能力,只需点击设计按钮,新的滤波器立即产生,避免了传统滤波器设计的大量手工运算。并 用他设计出了满足性能要求的低通数字滤波器,实现了对加速度传感器干扰振动信号的滤除,解决了工程实际问题。(This thesis int roduces a digital filter designing method using signal processing toolbox in Matlab sof tware. It gives detailedly using specifications of FDATool graphical user interface ,when designing filter using FDATool ,you can com2 pare filter designing demand with filter character so as to adjust the parameter at any moment . For powerful operation function of the computer ,when the parameters are changed ,you only need point the design button ,new filter will be produced. In this way ,a mass of manual operation will be avoided. A good lowpass digital filter is designed using FDATool ,the filter can filter preferably the acceleration sensor vibration signal and resolve the engineering problem.)

基于元胞自动机的气体扩散程序，实时显示左右两侧粒子密度变化。(Based on Cellular Automata gas diffusion process, real-time display left and right sides of the particle density.)

Simulator of CDMA Transmission Simulink Matlab Model .(*.mdl)

《MATLAB统计分析与应用：40个案例分析》程序与数据第7章 的源代码：方差分析(" MATLAB statistical analysis and application: 40 Case Studies" program and data in Chapter 7 of the source code analysis of variance)

通过A*算法解决两点之间最优路径的问题，并进行了可视化设计(for the problem of the best route between two locations, a algorithm is proposed and Visualization is designed)

ODE function 求解一阶线性常微分方程(ODE function for solving first-order linear ordinary differential equations)

Compressive sampling is an emerging technique that promises to effectively recover a sparse signal from far fewer measurements than its dimension. The compressive sampling theory assures almost an exact recovery of a sparse signal if the signal is sensed randomly where the number of the measurements taken is proportional to the sparsity level and a log factor of the signal dimension. Encouraged by this emerging technique, this thesis briefly reviews the application of Compressive sampling in speech processing. It comprises the basic study of two necessary condition of compressive sensing theory: sparsity and incoherence. In this thesis, various sparsity domain and sensing matrix for speech signal and different pairs that satisfy incoherence condition has been compiled.

包括最小二乘法、SVM、神经网络、1_k近邻法,包括调制，解调，信噪比计算，最小均方误差（MMSE）的算法，一种流形学习算法（很好用），D-S证据理论数据融合，单径或多径瑞利衰落信道仿真，利用贝叶斯原理估计混合logit模型的参数。( Including the least squares method, the SVM, neural networks, 1 _k neighbor method, Includes the modulation, demodulation, signal to noise ratio calculation, Minimum mean square error (MMSE) algorithm, A fluid manifold learning algorithm (good use), D-S evidence theory data fusion, Single path or multipath Rayleigh fading channel simulation, Bayesian parameter estimation principle mixed logit model.)

一个matlab环境下编制的使用很方便的多目标程序(The preparation of a matlab environment is very convenient to use multi-objective procedure)