esprit_basic1

• Plot the noisy speech signal both in time-domain and frequency-domain. • 进行含噪语音信号的时频分析 • Design a proper filter to remove noise from the speech signal. • 设计合适滤波器进行去噪 • Plot the clean signal both in time-domain and frequency-domain. • 进行去噪后信号的时频分析 • Design a Reverberator using 4 Comb filters and 2 All-pass filters, as shown in the following Figure, to generate reverberated and reflected sound with the capability of passing it through an equalizer. • 设计一个混响器（用四个梳状滤波器和两个全通滤波器（下图所示））来产生回声（通过一个均衡器（用于调整频率的补偿和衰减））

该源码使用C4.5算法进行分类，该程序为matlab源码。(Classify using Quinlan s C4.5 algorithm)

fetal ecg detection using matlab

MATLAB编程图像低通滤波源码MATLAB programming source image low-pass filter(MATLAB programming image low-pass filter source MATLAB programming source image low-pass filter)

说明：  荷兰Delft大学开发的insar（干涉合成孔径雷达）图像处理部分源代码，用matlab编写的。(Netherlands Delft University developed insar (interferometric synthetic aperture radar) image processing part of the source code with matlab prepared.)

OPTIMISATION OF SIGNAL BY PARTICULE SWARM METHOD

programs for matlab in electrical engendering

Implement the split and merge procedure for segmenting

The main idea behind this book, and the incentive for writing it, is that strong connections exist between adaptive filtering and signal analysis, to the extent that it is not realistic—at least from an engineering point of view—to separate them. In order to understand adaptive filters well enough to design them properly and apply them successfully, a certain amount of knowledge of the analysis of the signals involved is indispensable. Conversely, several major analysis techniques become really efficient and useful in products only when they are designed and implemented in an adaptive fashion. This book is dedicated to the intricate relationships between these two areas. Moreover, this approach can lead to new ideas and new techniques in either field.

产生用于跳频通信系统中的m序列rs序列，包括它们的自相关和互相关性能分析(Produce frequency-hopping communication system for m-sequences rs sequences, including their autocorrelation and cross correlation performance analysis)