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一种变步长的lms算法实现，用MATLAB编写。(A variable step size lms algorithm, using MATLAB write.)

The purpose of this Primer is to help you begin to use MATLAB. It is not intended to be a substitute for the online help facility or the MATLAB documentation (such as Getting Started with MATLAB, available in printed form and online). The Primer can best be used hands-on. You are encouraged to work at the computer as you read the Primer and freely experiment with the examples. This Primer, along with the online help facility, usually suffices for students in a class requiring the use of MATLAB.

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试设计一个切比雪夫I型高通数字滤波器，采样率为8000Hz,fp=1000Hz,fs=700Hz,Rp=3dB,Rs=20dB。(Try to design a type I Chebyshev high-pass digital filter sampling rate of 8000Hz, fp = 1000Hz, fs = 700Hz, Rp = 3dB, Rs = 20dB.)

含有PUMA560（机械臂）的MATLAB仿真教程以及官方的Robotic Toolbox教程(MATLAB simulation tutorials containing PUMA560 (robotic arm) and official Robotic Toolbox tutorial)

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针对滚动轴承故障信号具有非平稳、非高斯的特点，提出了将时域分析与小波分析相结合的方法对滚动轴承进行故障诊断。在研究不同信号分析方法理论的基础上，以滚动轴承外圈故障振动信号为例，采用多种信号处理方法进行了分析。结果表明，各种分析方法在分析轴承故障时的特点各不相同，在实际使用中，可将时域分析与小波分析综合使用，实现轴承状态的实时监测与故障的准确定位。(For rolling bearing fault signals have non-stationary, non-Gaussian, we proposed the time-domain analysis and wavelet analysis method of combining the rolling element bearing fault diagnosis. In the study of different analytical methods based on the theory of signal to the outer ring rolling bearing fault vibration signal, for example, using a variety of signal processing methods are analyzed. The results show that a variety of analytical methods in the analysis of the characteristics of bearing failure vary, in actual use, can be time-domain analysis and synthesis using wavelet analysis, to achieve accurate positioning of the bearing condition monitoring and real-time fault.)

基于非参数概率密度估计的盲源分离算法（NpICA），使用matlab编程，有可视界面。(Non-parametric probability density estimation-based blind source separation algorithm (NpICA), using the Matlab programming, visual interface.)

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program for fingerprint recognition using minutia The general shape of the fingerprint is generally used to pre-process the images, and reduce the search in large s. This uses the general directions of the lines of the fingerprint, and the presence of the core and the delta. Several categories have been defined in the Henry system: whorl, right loop, left loop, arch, and tented arch. Most algorithms are using minutiae, the specific points like ridges ending, bifurcation... Only the position and direction of these features are stored in the signature for further comparison.