sas

all possible ways of choosing k elements out of the numbers 1:n without duplications(all possible ways of choosing k elements ou not one of the numbers : n without duplications)

control of motor in matlab simulink

独立分量分析（ICA）以非高斯源信号为研究对象，在统计独立的假设下，对多路观测到的混合信号进行盲信号分离，已广泛应用于无线通信、生物信号提取、语音信号处理、图像处理和噪声抑制等领域。 (The independent component analysis (ICA) addresses non-Gaussian source signals under amusing independent each other, it performs blind separation for multi-channel observed signals. It has widely applied in wireless communication, biological signals extraction, audio signal processing, image processing, and noise reducing and so on.)

fs = 8000 t = (0:1/fs:1). x1 = cos(2*pi*t*300) x2 = cos(2*pi*t*400) ha = phased.ULA( NumElements ,10, ElementSpacing ,1) ha.Element.FrequencyRange = [100e6 300e6] fc = 150e6 x = collectPlaneWave(ha,[x1 x2],[10 20 45 60] ,fc) rng default noise = 0.1/sqrt(2)*(randn(size(x))+1i*randn(size(x))) hdoa = phased.ESPRITEstimator( SensorArray ,ha,... OperatingFrequency ,fc) doas = step(hdoa,x+noise) az = broadside2az(sort(doas),[20 60])

自己编写的卡尔曼滤波算法，大家可以参考下。(I have written the Kalman filter algorithm, we can refer to.)

15为ADC在simulink环境下的建模(model of 15bit adc in simulink)

一种改善HHT端点效应的新方法及其在电能质量中的应用_苏玉香(A new method to improve the end effects of HHT and its application in power quality _ Su Yuxiang)

ACO相关编程文档和，光通信的相关论文一篇希望对大家有所帮助。(ACO optic communication and one paper)

里面有大量的Matlab的应用实例，可以给大家的学习带来帮助，它不仅适合初学者而且也可以提高大家的Matlab编程能力。(Which a large number of Matlab application example, can help to bring everyone to learn, not only for beginners but also can improve our ability to Matlab programming.)

利用该程序，只要把已知低通滤波器的系数输入，就可画多小波的尺度函数的图象。(Use of the procedure, known as long as the low-pass filter coefficients input, can draw Multiwavelet image scaling function.)