DSP

RS编码的例子，可以参考这个学RS编码,可以参考通信原理的书籍来对照来学！(This is a example about RS coding ,and you can learn RS by that.)

Contourlet去噪的程序。实现了图像的多尺度分解下的去噪与重建。(Denoising procedure Contourlet)

DSP程序里IIR滤波结果跟MATLAB仿真结果相差很大是为什么?各位老兄: 我最近利用TI库函数里IIR滤波程序对一组数据进行滤波,IIR系数利用TI公司所提供的eziir.m(matlab程序)程序获得,在matlab里利用相同的系数对相同的数据进行滤波(DSP program results IIR filter with MATLAB simulation results are very different and why? You man: I have the use of library functions in TI procedures IIR filter to a group of data filtering, IIR coefficients provided by the use of TI' s eziir.m (matlab program ) procedures in matlab using the same coefficient in the same data filtering)

不错的源代码，喜欢matlab实验的朋友可以下载下来看看：） --模拟弹簧振子(Good source code, like matlab experiment to see if a friend can download it:) Simulation of Spring Oscillator)

手工指定节点的编号以及位置之后，可以自动生成节点的坐标，以及杆的左右节点，不需要手动输入。(make the topology of truss)

这是模式识别中最小风险Bayes分类器的设计方案。在参考例程的情况下，自行完善了在一定先验概率的条件下，男、女错误率和总错误率的统计，放入各个数组当中。 全部程序由主函数、最大似然估计求取概率密度子函数、最小错误率贝叶斯分类器决策子函数三块组成。 调用最大似然估计求取概率密度子函数时，第一步获取样本数据，存储为矩阵；第二步对矩阵的每一行求和，并除以样本总数N，得到平均值向量；第三步是应用公式（3-43）采用矩阵运算和循环控制语句，求得协方差矩阵；第四步通过协方差矩阵求得方差和相关系数，从而得到概率密度函数。 调用最小风险贝叶斯分类器决策子函数时，根据先验概率，再根据自行给出的5*5的决策表，通过比较概率大小判断一个体重身高二维向量代表的人是男是女，放入决策数组中。 主函数第一步打开“MAIL.TXT”和“FEMALE.TXT”文件，并调用最大似然估计求取概率密度子函数，对分类器进行训练。第二步打开“test2.txt”，调用最小风险贝叶斯分类器决策子函数，然后再将数组中逐一与已知性别的数据比较，就可以得到在一定先验概率条件下，决策表中不同决策的错误率的统计。 (This is a pattern recognition classifier minimum risk Bayes design .In reference to the case of routine , self- improvement in a certain a priori probability conditions, male , female and total error rate error rate statistics , into which each array . All programs from the main function , maximum likelihood estimation subroutine strike probability density , the minimum error rate Bayesian classifier composed of decision-making three subfunctions . Strike called maximum likelihood estimate probability density subroutine , the first step to obtain the sample data , stored as a matrix the second step of the matrix, each row sum , and divided by the total number of samples N, be the average vector The third step is the application of the formula ( 3-43 ) using matrix and loop control statements , obtain the covariance matrix fourth step through the variance-covariance matrix and correlation coefficient obtained , resulting in the probability density function . Bayesian classifier )

alab document on ASK PSL and QPSK modulation techniques

matlab for communication

利用matlab做的永磁同步电机的模型，给定转速做外环，输出稳定(Matlab to do a permanent magnet synchronous motor model given speed to do the outer ring, stable output)

array gain of MRC in a Rayleigh fading channel