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说明：  旋转图像，平滑会出现的锯齿，例子和源代码(Rotate the image, smoothing jagged occur, examples and source code)

说明：  利用matlab的gui设计的带有输入和输出功能的界面图形，可视性很强，自己独立编写的数据和图形，学习非常值得(Uses the Matlab GUI design to have the input and output function the interface graph, the visibility is very strong, the data and the graph which oneself compiles independently, the study is very worthwhile.)

非线性光纤光学中文教程，深入浅出，本人看完以后觉得收益很大。(Nonlinear fiber optics Chinese guide, a simple, I think after reading a great income.)

matlab code,solve equations using gauss method.

IEEE802.16标准系统的仿真，包括发射机，信道，接收机这个完整的过程(simulation of ieee802.16 standard)

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)

光学工程类Matlab模拟程序，模拟了2N个透镜阵列的成像(Optical Engineering Matlab simulation program to simulate a lens array of imaging 2N)

MATLAB100个编程实例 易读MATLAB100个编程实例 易读MATLAB100个编程实例 易读(very good very goodvery good)

matlab coding for personal communication in embedded system

DD算法实现语音增强，噪声谱估计，根据寂静帧和后面能量的对比来估计(DD algorithm speech enhancement, noise spectrum estimation, based on comparative silence frame and rear energy to estimate)