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基于MATLAB的近似熵程序,主要用与生物信号的检测,主要用于生物医疗工程的信号处理方面(matlab program for calculating approximate entropy in biomedical signal processing especially.)

优秀论文及配套源码。Hilbert-Huang变换(HHT)是一种新的非平稳信号处理技术，该方法由经验模态 分解(EMD)与Hilbert谱分析两部分组成。任意的非平稳信号首先经过EMD方法处理后被分解为一系列具有不同特征尺度的数据序列，每一个序列称为一个固有模态函数(IMF)，然后对每个IMF分量进行Hilbert谱分析得到相应分量的Hilbert谱，汇总所有Hilbert谱就得到了原信号的谱图。该方法从本质上讲是对非平稳信号进行平稳化处理，将信号中真实存在的不同尺度波动或趋势逐级分解出来，最终用瞬时频率和能量来表征原信号的频率含量。 本文研究了基于HHT的暂态电能质量扰动检测方法，介绍了HHT的基本原理和利用HHT检测电能质量多扰动信号的实现方法。仿真试验表明该方法可以实时检测扰动的起止时刻，持续时间和扰动幅度，适用于电能质量多扰动的监测和辨识系统。 (Hilbert-Huang Transform(HHT) is a new non-stationary signal processing technology，including the Empirical Mode Decomposition(EMD) and Hilbert spectral analysis．In this method，arbitrary non-stationary signals was divided into a series data sequence with different characteristic scales after the first EMD treatment，each sequence is called an intrinsic mode function(IMF)，and then each IMF component gained corresponding the Hilbert spectrum though Hilbert spectrum analysis，a summary of all Hilbert spectrum assembled to the spectra of the original signal．In essence，this method is a stable processing for non-stationary signal，which decomposed the different fluctuations or trends in the signal in rum，and represented the frequency content of the original signal using the final instantaneous frequency and energy． This paper study a method to detect power quality disturbances based on the HHT，in which the principle and the realization of the HHT and the realization of power quality disturbance)

通过极坐标变换获得图像的中心投影曲线，然后利用傅里叶变换获得图像的不变特征，从而实现对发生形变的物体的识别。(Polar coordinates to obtain the image through the center of projection curve, and then Fourier transform to obtain images of the same features, enabling the identification of objects deformation occurred.)

MATLAB小波分析高级技术2006电子书，书中内容较为实用(MATLAB Wavelet Analysis Advanced Technology 2006 books, the book is more practical content)

this code implementation radar.

一种快速超分辨算法,这一方法在频域完成反卷积运算，比一般算法快许多。(fast super-resolution in frequency domain)

It is a 4-bit adpcm. This is a simple illustration of how compression can be achieved more than pcm.

it s code about sub-band coding in matlab

for using this code need to use signal toolbox and general toolbox in your matlab Using Haar transform to compress the image (showing remaining coefficen of Thresholded Image) and then using Inverse 2D Haar transform and finding the SNR to see how well decompression works

APSK仿真程序，包括收端、发端、信道，以及(APSK simulation program, including land-side, the originator, channel, as well as)