Digital-film-with-detection-system

该Matlab程序给出了Schmidt-Kalman filter和标准Kalman filter之间的性能对比，不是函数的形式，是直接的可执行程序，如有需要，直接更改文件中的参数就可以了(The Matlab program gives the Schmidt-Kalman filter and standards of performance comparison between the Kalman filter is not a function of the form is directly executable program, if necessary, change the file directly to the parameters can be a)

“基于Floyd最短路算法的Ford和Fulkerson迭加算法”的最小费用最大流算法，其基本思路为：把各条弧上单位流量的费用看成某种长度，用Floyd求最短路的方法确定一条自V1至Vn的最短路；再将这条最短路作为可扩充路，用求解最大流问题的方法将其上的流量增至最大可能值；而这条最短路上的流量增加后，其上各条弧的单位流量的费用要重新确定，如此多次迭代，最终得到最小费用最大流。 (" Floyd shortest path algorithm based on the Ford and Fulkerson algorithm superposition" of the minimum cost maximum flow algorithm, the basic idea is: the flow of each arc on the unit cost as a length, with Floyd for the most short-circuit method to determine a from V1 to Vn of the most short-circuit then this can be expanded as the shortest way, by solving the maximum flow of traffic on the way to its maximum possible value and this increased the flow of the shortest path, on which the arcs of the unit to re-determine the cost of traffic, so several iterations, finally get the minimum cost maximum flow.)

numbers 1.15 in hexa

InTech Model_predictive_control_of_nonlinear_processes

测试可以跑，根据自己情况修改下函数即可. NSGA-III 首先定义一组参考点。然后随机生成含有 N 个（原文献说最好与参考点个数相同）个体的初始种群，其中 N 是种群大小。接下来，算法进行迭代直至终止条件满足。在第 t 代，算法在当前种群 Pt的基础上，通过随机选择，模拟两点交叉（Simulated Binary Crossover，SBX）和多项式变异 产生子代种群 Qt。Pt和 Qt的大小均为 N。因此，两个种群 Pt和 Qt合并会形成种群大小为 2N 的新的种群 Rt=Pt∪Qt。 为了从种群 Rt中选择最好的 N 个解进入下一代，首先利用基于Pareto支配的非支配排序将 Rt分为若干不同的非支配层（F1，F2等等）。然后，算法构建一个新的种群St，构建方法是从 F1开始，逐次将各非支配层的解加入到 St，直至 St的大小等于 N，或首次大于 N。假设最后可以接受的非支配层是 L层，那么在 L+ 1 层以及之后的那些解就被丢弃掉了，且 St FL中的解已经确定被选择作为 Pt+1中的解。Pt+1中余下的个体需要从 FL中选取，选择的依据是要使种群在目标空间中具有理想的多样性。(The test can run and modify the function according to its own situation. NSGA-III first defines a set of reference points. Then the initial population containing N individuals (preferably the same number of reference points as the original literature) was randomly generated, where N was the size of the population. Next, the algorithm is iterated until the termination condition is satisfied. On the basis of current population Pt, the algorithm simulates two-point crossover (SBX) and polynomial mutation to produce offspring population Qt by random selection.)

ofdm的详细仿真，包括信道，多径，及多部分的波形，详细的说明(OFDM detailed simulation, including channel, multi-path, and multi-part of the waveform, a detailed description of)

Simple Genetic Algorithm

冈萨雷斯书籍图像库 图像的基本 一些李娜图像等等(Gonzalez basic image image library books)

sdof vibraion analysis

多事例维度约简的matlab程序及其数据。(Many examples of dimension reduction matlab program and its data.)