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滤波器设计示例：matlab设计IIR基本示例，matlab设计IIR高级示例，matlab窗函数设计FIR滤波器基本示例。(Filter Design Example: matlab basic sample design of IIR, matlab advanced example of IIR design, matlab window function, the basic design of FIR filter example.)

Introduction to Statistical and Adaptive Signal Processing – Random Signals – Spectral Estimation – Signal Modeling – Adaptive Filtering • Course Overview – Course Outline – Textbook – References

基于KNN算法的鸢尾花分类代码，可一直在matlab上运行。(Iris classification code based on the KNN algorithm, has been running in matlab.)

用MATLAB实现FIR，包括常用窗函数代码(Using MATLAB FIR, including the commonly used window function code)

GPS信号捕获 指标是signalpower=-185dBW，此时可以进行室内定位(GPS signal acquisition indicator is signalpower =-185dBW, indoor positioning can be performed at this time)

A Novel Approach to Design and Implement Dierential Time Lapse Video in Real Time Application

ADC动态参数测试的matlab程序，可以测试DNL，INL，ENOB，SFDR等(ADC dynamic parameter test matlab program, you can test DNL, ​ ​ INL, ENOB, SFDR, etc.)

- for floating point to fixed point - seperate to integer and fraction part

在计算机上产生一组实验数据，首先产生一段零均值白噪声数据u（n）,令功率为 ，让u(n)通过一个三阶FIR： 得到y(n). .y(n)上加三个实正弦信号f1’=0.1,f2’=0.25,f3’=0.26调整 和正弦信号幅度信噪比大致为10dB,50dB,50dB. (1) 令N=256,描绘xn波形； (2)得出真实功率谱密度 . (3) 利用此实验数据Pisarenko谐波分解法估计该实验数据的正弦频率及幅度。 (On the computer to generate a set of experimental data, first generate a zero mean white noise data u (n), so that power, let u (n) through a third-order FIR: get y (n).. Y (n) added three real sinusoidal signal f1 ' = 0.1, f2' = 0.25, f3 ' = 0.26 and sine signal amplitude adjustment signal to noise ratio is approximately 10dB, 50dB, 50dB. (1) that N = 256, depicted xn waveform (2) the true power spectral density obtained. (3) using this experimental data, Pisarenko harmonic decomposition method to estimate the experimental data of the sinusoidal frequency and amplitude.)

此为模式识别中Parzen窗法估计概率密度函数。 全部程序流程如下： 1、读取FAMALE.TXT文件把身高或体重给数组，并求x1的样本数N1和窗宽、体宽； 2、读取MALE.TXT文件把身高或体重给数组，并求x2的样本数N2和窗宽、体宽； 3、读取Test2.txt文件把对应的身高或体重给数组A并求A的样本数M； 4、利用Parzen窗法估计概率密度函数判别男女性别； 5、对本判别的错误率进行统计。 (This is the pattern recognition Parzen window method to estimate the probability density function . All program flow is as follows : 1 , read FAMALE.TXT file to height or weight to the array, and find the number of samples x1 N1 and window width , body width 2 , read MALE.TXT file to height or weight to the array, and find the number of samples x2 N2 and window width , body width 3 , read Test2.txt file to the corresponding height or weight requirements for the array A and A is the number of samples M 4 , the use of Parzen window method to estimate the probability density function of gender discrimination 5 , determine the error rate of the statistics . )