KASAMI-matlab-code

利用Simulink对变电站电压无功综合模糊控制的仿真,(Using Simulink integrated substation voltage and reactive power fuzzy control simulation,)

三维实体单元刚度矩阵matlab源程序，通用代码(The 3-D solid element stiffness matrix of Matlab source program)

This code contain the gist descriptor in matlab

对录音信号集 中的某一语音，利用BATLAB设计一美尔例谱算法，并实现。 取信号集 中的一个语音信号：“xxxxxx”，将它作为输入的语音信号来为设计一个美尔倒谱算法，在该算法中，主要设计了以下环节： 1.读入一个语音信号；2.对这个信号归一化；3.对归一化的信号进行加窗处理（这里的矩形窗长度必须为257，重帧长64）；4.进行预加重处理，即通过一个高通滤波器： ；5进行512点的FFT；6.分别取模平方得到功率谱；7.在设计的mel滤波器组中，我采用了25个带通滤波器；8.将得到的功率谱信号通过mel滤波器组，得到相应的25个功率值；9.对这些功率值取自然对数；10.对这些值取离散作弦变换；11.将得到的值去掉直流分量，取其它值作为MFCC参数。 (Concentrated on recording a voice signal, using BATLAB designed Mayer cases spectral algorithm, and implementation. Get a voice signal signal focus: "xxxxxx", will it as input for the design of a voice signal to Mel Cepstrum algorithm in the algorithm, the main design of the following links: 1. Read a speech signal 2. On the signal normalized 3. Of the normalized windowed signal processing (here, rectangular window length must be 257, re-frame size 64) 4. For Pre-emphasis processing through a high-pass filter: 5 for 512 points of FFT 6. modulo square were obtained spectrum 7. in the design of mel filter banks, I use a 25 band-pass filter 8 . will be the power spectrum signal by mel filter bank, corresponding to the 25 power values 9. on the power to take the natural logarithm value 10. to take these values as strings of discrete transform 11. will be of value to out DC component, to take other values as MFCC parameters.)

应用Matlab计算边界条件，解决最优控制问题。(Matlab Boundary Conditions )

无线传感器能量高效路由算法－LEACH算法(Energy efficient routing algorithm for wireless sensor-LEACH algorithm)

粗糙集课件。里面有覆盖粗糙集模型和 Ziarko变精度粗糙集模型以及粗糙集程序(courseware. There are covering rough set model and Ziarko model)

本书介绍了C++实用编程技术和最佳的实践方法，深入研究了异常处理。(This book describes the practical C++ programming techniques and best practices, in-depth study of exception handling.)

Creates the data for a smooth line going through the points given

傅里叶变换过程中由于时域信号长度有限，变换后有可能漏掉大的频谱分量(Fourier transform process, due to the finite length of the time domain signal, after conversion may miss a large spectral components)