Radar_system_simulation

matlab基于KF和EKF的工具箱描述(Optimal fi ltering with Kalman fi lters and smoothers – a Manual for Matlab toolbox EKF/UKF)

潮汐调和分析，用于海洋专业，分析各分潮潮汐调和常数。(Tidal harmonic analysis for marine professionals to analyze the sub-tidal tidal harmonic constants.)

SVM简单算法，利用该算法可以实现简单的几类数据的分类问题，非常简便(SVM simple algorithm, using this algorithm can achieve a simple classification of data types, very simple)

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)

Overcomplete wavelet transform using w53

读取轴承全寿命周期中的每组数据，并对其进行多域特征提取，包括时域和频域特征提取，用于轴承性能退化评估的研究很有用，自己亲手调试成功(Read bearing the full life cycle of each set of data, and extract its multi-domain characteristics, including time domain and frequency domain feature extraction for bearing performance degradation assessment studies are useful)

Calendar Data Source Code for Andriod.

用于自适应天线的稳健的RLS算法，保证天天的抗干扰能力(Robust RLS algorithm for adaptive antennas, ensuring every anti-jamming capability)

应用于matlab支持向量机svm的工具箱(Applies to support vector machine SVM matlab toolbox)

这是一个基于贪婪算法和右手法则基础上得到的路由仿真程序。对于初学者还是有借鉴意义的！(Greedy Perimeter Stateless Routing for Wireless Networks and right hand rule )