crack_Hudson

matlab code a tester

一种频率估计新算法的仿真可以在dot内高精度的测量频率信号(matlab dot muisc )

image clustering file

本书基于MATLAB 5.2版，提供了使用MATLAB的实践性指导。MATLAB已成为适合多学科、多种工作平台的功能强大、界面友好、语言自然并且开放性强的大型优秀应用软件，同时也已成为国内外高等院校高等数学、数值分析、数字信号处理、自动控制理论以及工程应用等课程的基本教学工具。本书按逻辑编排，自始至终用实例描述；内容完整且每章相对独立；是一本简明的MATLAB参考书，既适用于初学者，也适用于高级MATLAB用户。对MATLAB与FORTRAN、C等语言结合的描述更是所有MATLAB书籍中少有的一大特色。 本书适合作为理工科高等院校研究生、本科生教学用书，也可作为广大科研工程技术人员的自学用书。(MATLAB users. Of MATLAB and FORTRAN, C and other languages with a description of all MATLAB books is a major feature of the few. This book is suitable as a science and engineering colleges and universities graduate, undergraduate teaching books, but also the majority of scientific research and engineering and technical personnel as self-study book.)

The aim of the assignment is to understand the concept of the image enhancement stage We need to know the technique to improve the image or better input for the image processing technique as in the assignment. In the first part of the assignment is the segmentation using thresholding technique. Before we threshold the image, we need to prepare the better image for input such as histogram equalization to stretch the intensity value of the image before converting to binary image. In the second part of the assignment is about frequency domain. We need to transform the spatial image to frequency image using Fourier transform of the image before using the filter.

迭代求图像最佳分割阈值的算法 迭代求图像最佳分割阈值的算法(Iterative threshold image segmentation algorithm for optimal Iterative threshold image segmentation algorithm for optimal)

最小二乘法形函数及其应用包括函数模拟绘图(the least square )

经典matlab教材《数字信号处理及其matlab实现》电子书(Matlab classic textbook " Digital Signal Processing and its matlab implementation," e-books)

葛哲学编著《小波分析理论与MATLABR2007实现》的所有源代码·包含大量的实例和典型应用(some refer for lisp)

雷达信号的基本模型，高斯分布，几何分布，求信号的概率分布，概率密度函数，功率谱函数，自相关函数等等(The basic model of the radar signal, Gaussian distribution, geometric distribution, the probability distribution for the signal, probability density function, power spectrum, the autocorrelation function, and so)