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MATLAB for signal processing on multiprocessors and multicores.pdf

说明：  射频设计很好的MATLAB参考代码，对于参数设计提供了形象方便的途径(RF design of the MATLAB reference code good for the image parameter design provides a convenient way to)

a function that extract regions in MSER

256色转灰度图，用matlab实现一副彩色图像的灰度变换，但必须是bmp格式的图像(256-color to grayscale, using matlab to achieve a color image of the gray-scale transformation, but it must be bmp format images)

本文对变步长(VSS) 自适应滤波算法进行了分析,针对输入信号高度相关时算法收敛速度下降导致性能下降 的问题,提出了一种解相关变步长归一化LMS 自适应算法,引入相关性原理,使得算法保持良好的收敛性能。计算机仿真 结果与理论分析相一致(In this paper , we discuss and analyze the variable step2size adaptive algorithm(VSSLMS) ,in which the descent of it s convergence speed leads to the reduction of performance when input signals are heavily correlated . As a result , we propose an uncorrelated variable step2size normalized LMS adaptive algorithm. Due to the principle of correlation ,the algo2 rithm can achieve good performance. The simulations agree to the theoretical analysis.)

1．用Matlab产生正弦波,矩形波,以及白噪声信号，并显示各自时域波形图 2．进行FFT变换，显示各自频谱图，其中采样率，频率、数据长度自选 3．做出上述三种信号的均方根图谱,功率图谱,以及对数均方根图谱 4．用IFFT傅立叶反变换恢复信号，并显示恢复的正弦信号时域波形图(1. Produce sine wave, square wave, and the white noise signal with Matlab, and their time-domain waveform display 2. FFT transform, display each spectrum, where the sampling rate, frequency, length optional data 3. RMS to make maps of the three signals, power spectrum, as well as the number of RMS map 4. Restored by inverse Fourier transform IFFT signal and displays the time domain waveforms sinusoidal signal recovery)

图形图像 匹配。当有两个图像时，程序计算一个图像的不变量，然后跟两一个图像比对，然后输出他们是否匹配。(This codes are for images matching when you have two or more images taken under different lighting, rotation...)

流体力学方法模拟双离子一维鞘层的matlab代码，可作为交流学习使用(Fluid dynamics simulation of one-dimensional dual ion sheath matlab code, can be used as learning to use exchange)

按照一定的要求和参数生成一级海杂波，主要用于雷达海杂波仿真。(Sea clutter level is generated in accordance with certain requirements and parameters, and generate graphics with matlab.)

Information Hiding Using Least Significant Bit Steganography and Cryptography