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这是张德丰《MATLAB概率与数理统计分析》随书源码(M文件)。代码包括的内容有：概率分布计算及统计特征、数字特征计算、统计图绘制(盒状图、散度图等)、点估计和区间估计、假设检验、方差分析、曲线拟合、回归分析、因素分析、聚类分析、正交实验设计分析、多元方差分析、判别分析、隐马尔可夫模型建模与参数估计和在语音识别中的应用。(This is Zhang Defeng " MATLAB Analysis of probability and mathematical statistics," with the book source (M file). The contents of the code include: calculation of the probability distribution and statistical characteristics, digital feature calculation, statistical mapping (box-shaped graph, scatter graph, etc.), point and interval estimation, hypothesis testing, analysis of variance, curve fitting, regression analysis, factor analysis, cluster analysis, orthogonal experimental design, multivariate analysis of variance, discriminant analysis, hidden Markov modeling and parameter estimation and application in speech recognition.)

比较经典的一个多核学习MKL代码（GMKL Generalized MKL），里面包含其对应的文章，很容易学习和调试！(Learn more classic a multicore MKL Code (GMKL- Generalized MKL), which contains the corresponding article, it is easy to learn and debug!)

维也纳科技大学的关于LTE的系统级仿真平台，可以作为初学者使用。(Vienna university of science and technology, the system about LTE level simulation platform, can be used as a beginner)

数字信号处理中的基于Monte Carlo的方法(Monte Carlo-based methods in signal processing)

图像处理MATLAB程序（教学使用）-图像灰度级修正（直方图均衡化）(MATLAB image processing program (Teaching)- image gray level correction (histogram equalization))

人体脉搏信号的有关数据及有关qrs群波探测的相关代码(The pulse signal of human body of relevant data and related group QRS wave detection related code)

16apsk通讯系统的信噪比与误码率计算并绘图(16APSK communications system signal to noise ratio and bit error rate calculation and mapping)

设有一个随机信号 服从AR(4)过程，它是一宽带过程，参数如下： 我们通过观测方程 来测量该信号， 是方差为1的高斯白噪声，用LMS算法和RLS算法通过观测方程来估计原信号。并用Matlab对此问题进行仿真。 (There is a random signal obedience AR (4) process, which is a broadband process parameters are as follows: We are measured by observing the signal equation is a Gaussian white noise variance, with the LMS algorithm and RLS algorithm to estimate the observation equation the original signal. This issue with Matlab simulation.)

Itti算法和他的文章。Itti提出的显著图模型是一种模拟生物体视觉注意机制的选择性注意模型,比较适合处理自然图像。(Itti algorithms and his article. Itti saliency map model proposed is a simulation of selective attention model organism visual attention mechanism, more suitable for processing natural images.)

C-均值聚类 BP神经网络信号分析与处理方法，对模拟产生的数据样本进行训(C-means clustering analysis and BP neural network signal processing method, the simulated data generated training samples)