14db3585364e

时频分析工具箱，作为补充MATLAB时频分析功能的源代码(Time-Frequency Analysis Toolbox as a supplementary function of time-frequency analysis MATLAB source code)

Tim_Bailey s SLAM m source code

Power Quality Improvement and Mitigation Case Study Using Distributed Power Flow Controller

Introduction to Programming Concepts with Case Studies in Python. – Introduction to Programming – Introduction to Programming Constructs – Introduction to Computer Science – Introduction to Computer Engineering

标准粒子群算法matlab程序，是粒子群优化发展的基础(Standard particle swarm optimization matlab program)

个集合遗传算法，蚁群算法，粒子群算法的混合算法解决TSP问题的MATLAB程序(Collection of genetic algorithm, ant colony algorithm for hybrid particle swarm optimization algorithm to solve TSP MATLAB program)

The main features of the considered identification problem are that there is no an a priori separation of the variables into inputs and outputs and the approximation criterion, called misfit, does not depend on the model representation. The misfit is defined as the minimum of the l2-norm between the given time series and a time series that is consistent with the approximate model. The misfit is equal to zero if and only if the model is exact and the smaller the misfit is (by definition) the more accurate the model is. The considered model class consists of all linear time-invariant systems of bounded complexity and the complexity is specified by the number of inputs and the smallest number of lags in a difference equation representation. We present a Matlab function for approximate identification based on misfit minimization. Although the problem formulation is representation independent, we use input/state/output representations of the system in order (The main features of the considered identification problem are that there is no an a priori separation of the variables into inputs and outputs and the approximation criterion, called misfit, does not depend on the model representation. The misfit is defined as the minimum of the l2-norm between the given time series and a time series that is consistent with the approximate model. The misfit is equal to zero if and only if the model is exact and the smaller the misfit is (by definition) the more accurate the model is. The considered model class consists of all linear time-invariant systems of bounded complexity and the complexity is specified by the number of inputs and the smallest number of lags in a difference equation representation. We present a Matlab function for approximate identification based on misfit minimization. Although the problem formulation is representation independent, we use input/state/output representations of the system in order)

说明：  matlab 产生带运动和噪声的退化图像(matlab generated with movement and noise degraded images)

有限时域差分 FDTD （susan ） 程序(FDTD Using FDTD (susan) program)

粗糙惩罚算法，此算法能够分辨光谱数据中的坏点，并对坏点加以惩罚，即减小该点的权重值，从而使得数据更加真实平滑。(Roughness Penalty Smoothing)