rs

系统辨识课上做的利用相关分析法辨识脉冲响应的实验。包括用M序列生成白噪声，计算互相关函数得到脉冲响应估计值等等，比较基础(Experiment about Identifying the pulse response with a method of correlative analysis in my class on system identification. It contains using M-sequence to generate white noise, bu calculating cross-correlation function to get impulse response estimates ect.)

说明：  tutorial explain matlab

在MATLAB中绘制不连续的COLORBAR,并方便根据自己喜好调节色彩(In MATLAB does not draw a continuous COLORBAR, and easily adjust colors according to their own preferences)

Gridding is a method of interpolating data from an arbitrary 2D sampling pattern to a uniform grid. In MRI, this allows rapid image reconstruction. There are numerous publications on MR gridding reconstruction. The tar file includes numerous .m scripts, and C code that can be compiled to a .mex function. You will need to compile the MEX functions - in Matlab try "mex gridlut_mex.c" and "mex calcdcflut_mex.c" These should result in files gridlut_mex.mex??? and calcdcflut_mex.mex??? where ??? depends on your operating system. Run the function spiralexample.m in Matlab. (Gridding is a method of interpolating data from an arbitrary 2D sampling pattern to a uniform grid. In MRI, this allows rapid image reconstruction. There are numerous publications on MR gridding reconstruction. The tar file includes numerous .m scripts, and C code that can be compiled to a .mex function. You will need to compile the MEX functions- in Matlab try "mex gridlut_mex.c" and "mex calcdcflut_mex.c" These should result in files gridlut_mex.mex??? and calcdcflut_mex.mex??? where ??? depends on your operating system. Run the function spiralexample.m in Matlab. )

粒子滤波算法在电池寿命预测中的应用，程序仿真(Application of particle filter algorithm in battery life prediction and program simulation)

混沌动力学初步对于刚开始接触混沌的人来说是个很好的书，希望对大家有用(Chaotic dynamics chaotic initial contact with the person who started it is a very good book, we want to be useful)

a exponential principal component analysis code.......

matlab for copula 最全的copula代码(matlab for copula)

增量SVM的实例，用于对手势的在线增量学习，有很详细的源码，并实现了SVM的多分类问题，对于模式识别和学习SVM有很大的帮助(Instance of the incremental SVM for gesture online incremental learning, there is a very detailed source, and to achieve a multi-SVM classification, pattern recognition and learning SVM great help)

fault detction and classification