交通标志检测matlab编程

本程序利用奇异值分解对3通道彩色图像进行压缩分解，具体步骤如下： 压缩过程： 1. 选取子图像大小K值，把图像分解成M×M个子图像，IMG(s),s=1,2,…, M2，其中M=N/K，原始图像IMG大小为N×N。 2. 计算这M2个子图像的平均值average，对每幅子图像减去均值图像得到新图像。 3. 计算相关矩阵R，其元素定义为 。 4. 计算R的特征值与特征向量，计算每幅子图像与最大特征向量的内积，便得到编码，即压缩后的图像。 (This procedure using singular value decomposition of 3-channel color image compression decomposition, concrete steps are as follows: compression process: 1. Select the sub-image size K value, the image is decomposed into M × M sub-image, IMG (s), s = 1, 2, ..., M2, in which M = N/K, the original image IMG size N × N. 2. M2 calculate the average of sub-image average, for each sub-image minus the new images mean images. 3. Calculation of correlation matrix R, defined as its elements. 4. Calculation of the characteristics of R value and eigenvector calculated each sub-image with the largest eigenvector of the inner product, they will have to code, that is, the compressed images.)

matlab初学者对于绘图的基本程序，比如画饼图，线图，向量图，瀑布图等基本绘图基础程序。(matlab for beginners a basic drawing program, such as yourselves chart, line graph, vector, waterfall and other basic drawing foundation program.)

给原始的语音信号加上一个高频余弦噪声，频率为5kHz。画出加噪后的语音信号时域和频谱图(To the original speech signal and the last high frequency cosine noise, frequency of 5kHz. Speech signal time domain and frequency spectrum and noise after the draw)

FBMC-OQAM频域实现的简单例程，使用PHYDYAS原型滤波器，供大家参考(ultraeasy implementation of FBMC-OQAM)

Gabor-function convolution masks are increasingly used in image processing and computer vision. This function simply computes the cosine and sine masks for a given width, period and orientation. The masks returned are properly normalised. It is not highly optimised - e.g. the symmetries are not used to reduce the computation. It is recommended that convolutions with these masks are done using CONVOLVE2 (available from Matlab File Exchange) to take advantage of their low rank. (Gabor-function convolution masks are increasingly used in image processing and computer vision. This function simply computes the cosine and sine masks for a given width, period and orientation. The masks returned are properly normalised. It is not highly optimised- e.g. the symmetries are not used to reduce the computation. It is recommended that convolutions with these masks are done using CONVOLVE2 (available from Matlab File Exchange) to take advantage of their low rank. )

自适应信号处理基础书籍以及仿真资料具备详细的说明(Adaptive Signal Processing)

人口增长（动物繁殖）模型，确定种群的固有增长率和稳定分布，建立稳定收获模型。 (it is about a model of population increasing)

sfbc ofdm Transmission

雷达信号瞬时自相关处理，计算信号瞬时频率，计算雷达信号参数等(instant auto-corelation)

遗传算法/大津法/区域生长法/迭代法分割图像,有详细注释，适合学习(Genetic algorithm/dajin method/area growth method/iteration method image segmentation, and have the detailed notes, suitable for learning )