chap5

用Kalman滤波方法估计目标航迹的Matlab源程序(this study is Kalman Filter algorithm of a very good process)

autocorrelation function for chirp signal

有向无环图程序，程序较为简洁，包含代码和简要说明。(Directed acyclic graph procedure is relatively simple, containing code and a brief description.)

可以用于求解两个信号的互信息、信息熵，并在此基础上求解广义相关系数。(Mutual information, information entropy can be used to solve the two signals, and solving the generalized correlation coefficient on this basis.)

State Space/ Kalman Filter Toolbox,Author: Marcelo Perlin / (PhD Student) / ICMA – Reading University,This toolbox was designed to simulate and fit linear state space models with the kalman filter approach. The main literature I used for this particular package is Kim and Nelson (1999) and Hamilton (1994).

牛拉法编程，是其在大电网多节点的网络中应用更方便(Cattle Rafah programming, is its application in multi-node network in a large grid is more convenient)

IMAGE PROCESING FAST FOURIER TRANSFORM

This file contains a whole package of Matlab simulation along with the results

针对粒子群优化算法应用于约束优化问题时易陷入局部极小值的问题, 提出了一种改进的粒子群优化算 法. 该算法综合了约束优化问题的目标函数值和约束函数的违反度值作为粒子群优化算法的双适应度值, 采用了 双适应值动态判断粒子群优化算法中粒子的优劣. 违反度值的计算引入了自适应加权系数, 相应地提出了调整各 权系数的自适应策略, 并改进了粒子群优化算法的粒子竞争选择策略, 拓展了粒子群优化算法的单适应值的应用 范围.应用约束自适应粒子群优化算法实现了城市水厂的节能优化调度. 结果表明, 该算法收敛速度快且结果可 靠. 粒子群优化算法为解决工程约束优化问题提供了一条可行途径(Considering that theparticleswarmoptimization( PSO) algorithmcanbeeasily trappedinto the local minimal valueinconstrainedoptimizationproblems, amodifiedconstrainedparticleswarmoptimiza
tionalgorithmwasproposed. Theobjective functionvalue andthe violationvalue of constraint functions wereeffectively combinedto formtwofitnesses, andthefitnesseswereadoptedto estimate if theparticle wassuperior or not ina dynamicway. Theadaptiveweight functionwasadoptedinthe calculationof the violationvalue. The strategy of keeping anadaptive relationof weight coefficientswasproposed, andthe strategyof swarmtournament selectionwasimproved. Theapplicationlocalizationsof thesinglefitnessof PSOwerewidenedaswell. ThemodifiedconstrainedPSOalgorithmwasappliedtosolveenergyoptimiza
tionproblemsof theurbanwater supplyprocess, whichshowedthat theconvergent speedof thealgorithm isfast andthe result isvalid. Afeasibleapproachto solvetheindustrial constraint optimizationproblems withPSOwasprovided.)

generation of chaotic signals (logistic map)