BUTTERWORTHfilters

EM algorithm for Gaussian Mixture Model

仿真产生OFDM信号；通过信道；实现解调。子载波用16QAM调制。(Simulation generate OFDM signals through the channel achieve demodulation. Subcarriers with 16QAM modulation.)

本函数用于面板空间滞后模型SAR及空间误差SEM模型的LM检验，提供稳健统计值。( Computes (robust) LM tests for spatial lag and spatial error)

说明：  matlab必备的源代码教程，希望能用的到(matlab)

房价的模拟与现实对比，得根据具体数据来对程序进行适当的调整，希望有用(Compare simulated and real house prices, by the specific data to make an appropriate adjustment to the program, seek to help)

说明：  一种基于量子相位编码的量子遗传算法，求解TSP(Quantum genetic algorithm)

QPSK及16QAM调制下的stbc，仅供初学者学习交流使用(QPSK and 16QAM modulation of the stbc, only for beginners to learn to share their)

模拟人的步行，是一个很好的模拟程序！！！( WALKER Human gait. This model, developed by Nikolaus Troje, is a five-term Fourier series with vector-valued coefficients that are the principal components for data obtained in motion capture experiments involving subjects wearing reflective markers walking on a treadmill. The components, which are also known as "postures" or "eigenwalkers", correspond to the static position, forward motion, sideways sway, and two hopping/bouncing movements that differ in the phase relationship between the upper and lower portions of the body. The postures are also classified by gender. Sliders allow you to vary the amount that each component contributes to the overall motion. A slider setting greater than 1.0 overemphasizes the characteristic. Can you see whether positive values of the gender coefficient correspond to male or female subjects?)

BPSK、QPSK误码率matlab仿真(BPSK, QPSK BER simulation matlab)

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 )