tuxiangchuli

说明：  这是论文“Saliency Detection: A Spectral Residual Approach”的matlab代码，其中包含两种代码，都可以运行，结果有点差异，大家可以试试。(This is the code of the paper“Saliency Detection: A Spectral Residual Approach”,and it includes two different codes which can be both run successfully ,and the results have some differences)

频率估计，用了最基本的Rife算法，和导数法。同时计算了平均频率和均方差值(Frequency estimation, using the most basic Rife algorithm and derivative method. The mean frequency and mean square difference are also calculated)

用matlab画图分析lamb波的原始激励信号和接收信号，并对比分析的差别(Using matlab drawing analyzes the original lamb wave excitation signal and the received signal, and compare the difference analysis)

考虑环境和经济的发电调度优化中的matlab程序(Consider the environmental and economic generation scheduling optimization in matlab program)

single tank model in matlab

The model used for creating the reference voltage is shown in Fig. 4. First, photovoltaic output current (Ipv) and output voltage (Vpv) are passed through a first order low pass filter with a magnitude of G = 1 and a time constant of T = 0.01 seconds in order to filter out the high frequency components or harmonics from these signals as shown in Fig. 5 and Fig. 6. The filtered current and voltage signals (Ipv_F and Vpv_F) are then fed into the MPPT control block that uses the Incremental Conductance Tracking Algorithm. An algorithm that is based on the fact the slope of the PV array power curve shown in Fig. 7 is zero at the Maximum Power Point (MPP), positive on the left of the MPP, and negative on the right. The MPP can thus be tracked by comparing the instantaneous conductance (I/V) to the incremental conductance (∆ I/∆ V) [11] as in (1):

基于matlab的微粒群优化算法解决多目标的问题。(Matlab-based particle swarm optimization algorithm to solve the multi-objective problem.)

2011年大学生数学建模竟赛A题答案（Matlab程序和数据文件）(2011 Mathematical modeling of race A question the answer (Matlab programs and data files))

说明：  NSGA2多目标优化算法，配上说明文档 NSGA-Ⅱ算法是 Srinivas 和 Deb 于 2000 年在 NSGA 的基础上提出的，它比 NSGA算法更加优越：它采用了快速非支配排序算法，计算复杂度比 NSGA 大大的降低；采用了拥挤度和拥挤度比较算子，代替了需要指定的共享半径 shareQ，并在快速排序后的同级比较中作为胜出标准，使准 Pareto 域中的个体能扩展到整个 Pareto 域，并均匀分布，保持了种群的多样性；引入了精英策略，扩大了采样空间，防止最佳个体的丢失，提高了算法的运算速度和鲁棒性。(NSGA2 multi-objective optimization algorithm, with instructions)

二自由度无阻尼振动的传统建模和解耦求解程序(Two degree of freedom undamped vibration of traditional modeling and decoupling solver)