SAR-Sign-alPProcessinMatlab

因此假设了一种机动目标模型：初始匀速直线阶段、匀速圆周运动阶段、返回匀速直线阶段，在此过程中线速度大小?v?保持不变。利用扩展卡尔曼（extended kalman filter, EKF）滤波算法进行定位跟踪，仿真结果表明，该假设模型既符合机动实际，又便于数学处理，并且滤波算法过程稳定，具有较快的收敛速度和较高的定位精度，提高了机动目标跟踪的精度和系统的实时性。(This paper proposes a maneuver target model: the initial phase of the uniform linear, uniform circular motion stage, returning to uniform linear stage, and the size of the line speed v remaining unchanged in this process. The extended Kalman filter (EKF) was used to track position, and simulation results show that the model is in line with the actual motor and easy to deal with the mathematics. The algorithm is stable and has rapid convergence rate and high positioning accuracy to improve the accuracy of the mobile target tracking and real?time system.)

Coaxial-Mesh generation-Finite element method-elctromagnetic-KNTU-

有详细的整数规划源代码，可以用于控制器参数寻优(Detailed integer programming source code, can be used for controller parameters optimization)

EPS控制模型 EPS控制模型 EPS控制模型 EPS控制模型(Control model control model EPS EPS EPS EPS control model control model)

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)

为领域专家提供一种有效的知识获取方法。 该方法 综合各种设备故障诊断知识获取方法的优点, 引入系统论的 概念和思想, 使知识获取过程系统化和程式化, 强调和引入 了设备对象功能技术物理效应、 伴随技术物理效应和可测性 研究。 提出的设备故障诊断模型知识获取方法已应用于建立 某一抽水蓄能机组的诊断知识模型, 表现出了操作的方便 性, 较好地解决了所获取知识的完备性和一致性问题。该方 法使设备故障诊断知识获取工作向工程化的方向迈进了一步(For the domain experts to provide an effective knowledge acquisition method. The fault diagnosis method of integration of knowledge acquisition method has the advantage, the introduction of the system of concepts and ideas, so that systematic and programmed process of knowledge acquisition, stress and the introduction of a functional device object technology physical effects, physical effects associated with technology, and testing research. Fault diagnosis model proposed knowledge acquisition method has been applied to establish the diagnosis of a Pumped Storage Unit knowledge model, showing the convenience of operation, can solve the access to knowledge of the completeness and coherence. The method makes the fault diagnosis knowledge acquisition work to project a step in the direction of)

通过Matlab编程，给定初始条件及PML边界条件，模拟VTI介质中地震波传播的波场快照。(The initial conditions and PML boundary conditions are given by programming with matlab.A snapshot of seismic wave propagation in VTI media is simulated.)

神经网络讲义，共八讲，主要讲述了神经网络发展史以及几个经典的人工神经网络(Neural network handouts, a total of eight speakers, mainly about the history of neural networks as well as several classic artificial neural network)

基于SVPWM的电机转速双闭环控制。波形完好，适合学习。(Double Closed Loop Control of Motor Speed Based on SVPWM. Waveform is good, suitable for learning.)

mathlab的三个分别灰色绝对关联度，相对关联度，归一关联度的代码，是三份M文件(mathlab absolute correlation of the three were gray, relative correlation, normalized correlation of the code, the file is three M)