kstest-testing

较为详细地介绍了延迟微分方程的概念以及数值解法，并提供具体的计算案例以及在matlab中的实现，并附有一定的源码，适合初学者参考学习()

用matlab实现混沌理论中的相空间重构代码，很好用的工具！(Chaos theory in phase space reconstruction using matlab code, very easy to use tool!)

本文主要讨论获得图片后如何提取其边界信息，首先利用图像灰度均匀化解决了对比度不清晰的问题，然后利用高斯滤波法对图片进行滤波去噪，进而利用Canny算法实现边缘检测提取边界，该方法与Matlab自带的求边界方法有明显的提高，为利用Matlab程序求图像分形维数提供了更精确的前提。(This article focuses on how to get the image to extract the boundary information, the first to use to the gray uniform solve the contrast is not clear, and then use the Gaussian filter image filtering noise, and then use the Canny edge detection algorithm to extract the boundary of the and Matlab comes boundary method has increased significantly, and provide a more accurate premise for the use of Matlab program for image fractal dimension.)

进行MATLAB的详细讲述以及各种程序的展示，对于初学者是很好的帮助(MATLAB described in detail and demonstrate the various programs, is very helpful for beginners)

50HZ陷波器的开发，开发环境为matlab。适合做课程设计。(The 50HZ notch developers, development environment for matlab. Suitable for curriculum design.)

matlab的地震声波正演，包括双程声波、单程声波。(Matlab seismic acoustic forward modeling)

超混沌系统的分岔图求解，内容详细易懂，可读性好(Hyperchaotic system to solve the bifurcation diagram, detailed easy to understand and readable)

这个利用matlab软件话三维连续系统的相图的程序，比如lorgenzeq系统的相图，也可以画超混沌的相图，(The matlab software using three-dimensional continuous system, then the phase diagram of the procedure, such as lorgenzeq system phase diagram, can also draw hyperchaos the phase diagram,)

matabl filtered high frequency noisy

该演示中包含的代码演示如何氡相似的功能，可以用来提高（以及部分）在Connectome电磁图像单元格边界。 请举出下列文件如果您发现此代码有用： Ritwik库马尔，阿梅里奥五雷纳和Hanspeter Pfister说“氡样的特点及其应用Connectomics”，接受，IEEE计算机学会研讨会在生物医学图像分析（MMBIA）2010年数学方法 http://seas.harvard.edu/〜 rkkumar radonLikeFeaturesDemo.m：演示边缘增强用氡相似的功能， getEdgeFeatures.m：助手为高斯函数的二阶导数滤波器 makeBarFilters.m：助手为高斯函数的二阶导数滤波器 sample.png：示例图像在此演示使用(The demo included in the code demonstrates how Radon-Like Features can be used to enhance (and segment) cell boundaries in Connectome EM images. Please cite the following paper if you find this code useful: Ritwik Kumar, Amelio V. Reina & Hanspeter Pfister, “Radon-Like Features and their Application to Connectomics”, accepted, IEEE Computer Society Workshop on Mathematical Methods in Biomedical Image Analysis (MMBIA) 2010 http://seas.harvard.edu/~rkkumar radonLikeFeaturesDemo.m : Demonstrates edge enhancement using Radon-Like Features getEdgeFeatures.m : Helper function for Gaussian Second Derivative Filters makeBarFilters.m : Helper function for Gaussian Second Derivative Filters sample.png : Sample image for use in this demo )