rp095_ICECT2012-E190

A implementation of Least Square Generalized

实现了图像处理中的频域低通处理，适合图像处理的初学者。matlab实现。(Image processing to achieve a low-pass frequency domain processing, image processing for beginners. matlab implementation.)

This is my power electronic lecture note on diode rectification.

Noise estimator for SENSE MRI The Maximum Spacing Noise Estimation in Single-coil Background MRI Data Signal Dependent Noise Level Estimation Fast Noise Estimation in Images Detail Preserving Anosotropic Diffusion for Speckle Filtering (DPAD) 2-D adaptive noise-removal filtering Noise estimators for MRI data Toolbox Noise estimation rician noise corrupted images

说明：  近年来，基于启发式的多目标优化技术得到了很大的发展，研究表明该技术比经典方法更实用和高效。有代表性的多目标优化算法主要有NSGA、NSGA-II、SPEA、SPEA2、PAES和PESA等。粒子群优化(PSO)算法是一种模拟社会行为的、基于群体智能的进化技术，以其独特的搜索机理、出色的收敛性能、方便的计算机实现，在工程优化领域得到了广泛的应用，多目标PSO(MOPSO)算法应用到了不同的优化领域[9~11]，但存在计算复杂度高、通用性低、收敛性不好等缺点。 多目标粒子群（MOPSO）算法是由CarlosA. Coello Coello等在2004年提出来的(In recent years, heuristic-based multi-objective optimization technology has been greatly developed, and research shows that this technology is more practical and efficient than classical methods. Representative multi-objective optimization algorithms mainly include NSGA, NSGA-II, SPEA, SPEA2, PAES and PESA. Particle Swarm Optimization (PSO) algorithm is an evolutionary technology based on swarm intelligence that simulates social behavior. With its unique search mechanism, excellent convergence performance, and convenient computer implementation, it has been widely used in the field of engineering optimization. The objective PSO (MOPSO) algorithm is applied to different optimization fields [9~11], but it has shortcomings such as high computational complexity, low versatility, and poor convergence. The multi-objective particle swarm optimization (MOPSO) algorithm was proposed by Carlos A. Coello Coello et al. in 2004)

分布傅里叶算法，可以用于多种计算，比如光孤子的特性分析(split_step_fourier_method.m)

仿真了LMS算和和牛顿算法以及最速下降算法有图形可以清楚的看到几个算法的收敛速度的快慢(Calculation and simulation of the LMS and Newton algorithm and the steepest descent algorithm can clearly see several graphical convergence of the algorithm for the pace of)

一个用MATLB编写的关于人脸识别中的2DPCA算法的程序(The preparation of a use MATLB 2DPCA on face recognition algorithm in the program)

Motion estimation algorithm - three step search

利用matlab处理图像，分别用高斯滤波，均值滤波和中值滤波，对同一个噪声图像处理及得到结果(Using matlab image processing, respectively, with a Gaussian filter, mean filter and median filter, image processing on the same noise and get results)