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说明：  n个点电荷电场线的matlab仿真 分别有1个 2个等（可以通过改变程序数字来得到相应的仿真结果）(Matlab simulation of N-point charge electric field lines)

实现了对10个数字音的识别，是学习PCA特征提取的很好的学习资料，包括调制，解调，信噪比计算。( To achieve the recognition of 10 digital sound, Is a good learning materials to learn PCA feature extraction, Includes the modulation, demodulation, signal to noise ratio calculation.)

程序代码说明 P0401：用Prewitt算子检测图像的边缘 P0402：用不同σ值的LoG算子检测图像的边缘 P0403：用Canny算子检测图像的边缘 P0404：图像的阈值分割 P0405：用水线阈值法分割图像 P0406：对矩阵进行四叉树分解 P0407：将图像分为文字和非文字的两个类别 P0408：形态学梯度检测二值图像的边缘 P0409：形态学实例——从PCB图像中删除所有电流线，仅保留芯片对象(Program code description P0401: Detects the edge of an image with the Prewitt operator P0402: LoG operator with different σ values is used to detect the edge of the image P0403: Detects the edge of an image with the Canny operator P0404: Threshold segmentation of the image P0405: Image segmentation using watermark threshold method P0406: Quadtree decomposition of the matrix P0407: The image is divided into text and non-text of the two categories P0408: Morphological gradient detects the edge of a binary image P0409: Morphology Example- Deletes all current lines the PCB image, leaving only the chip object)

SVM实现数据分类，可自行选取核函数，用于图像分割操作。程序可自动训练分类平面。(SVM for data classification, are free to select the kernel function，For image segmentation operation. The program can automatically train classifiers plane.)

SAR杂波统计建模方面的源程序，不仅可以能为SAR图像去噪工作提供数据源，更是研究SAR图像分割方面的很好的工具。(SAR clutter statistical modeling of the source, not only for SAR image denoising can provide the data source, but also aspects of SAR image segmentation a good tool.)

采用最小交叉熵，最大熵，OTSU阈值分割(Using minimum cross entropy, maximum entropy, OTSU thresholding)

模糊聚类分割主函数及demo，直接运行就行，当然要有图片，呵呵(Main functions and fuzzy clustering segmentation demo, run directly on the line, of course, have pictures, Oh)

多幅图像的加密技术 matlab源代码(image encryption technology Matlab source code)

the best program to estimait your powr to use matlab in image and sound traitment

一种简单高效地基于压缩感知的跟踪算法。首先利用符合压缩感知RIP条件的随机感知矩对多尺度图像特征进行降维，然后在降维后的特征上采用简单的朴素贝叶斯分类器进行分类。该跟踪算法非常简单，但是实验结果很鲁棒，速度大概能到达40帧/秒(A simple and efficient tracking algorithm based on compressed sensing. Firstly, with the random sensing matrix compressed sensing RIP conditions for multi-scale image feature dimension reduction, and then use the naive Bias classifier simple classification in the feature reduction after the. The tracking algorithm is very simple, but the results are robust, speed can reach 40 frames per second)