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This book constitutes an excellent source for understanding the basic operation of the Global Positioning Systems (GPS). It also allows the reader to take the first steps towards understanding how the Kalman Filter is implemented in the estimation of drifting parameters of the GPS. The "Kalman Filter Basics" chapter is preceded by a description of the different errors that affect the GPS signals. Furthermore, this book includes sections on the Wide-Area Augmentation System, Inertial Navigation, and Differential GPS, which enables the understanding of these concepts and thus, provides the reader an overall perspective of the Global Positioning System.

说明：  双馈电机数学模型，基于simulink，如果需要可以提供S函数的模型(Doubly-fed machine mathematical model, based on simulink, if necessary can provide a model S function)

这是基于matlab的信号系统实验程序，可以完成信号系统课程的相关实验，提高信号系统课程的认识和理解。(This is based on the signaling system matlab experimental procedure, you can complete courses related experiments signaling system, improve the signal system course knowledge and understanding.)

阵列信号处理中信源数目的AIC编码的实现程序，用于确定信源的个数。(Array signal processing in the source number is encoded in the AIC implementation procedures, used to determine the number of source . )

各种雷达脉冲压缩信号的时域，频域以及模糊函数仿真(A variety of radar pulse compression signal in time domain, frequency domain as well as the ambiguity function simulation)

matlab algorithm，PCA (Principal component analysis)used for dimensionality reduction. usage:[NEW_DATA, EIGVECTOR, EIGVALUE] = PCA(DATA, EIG_N)

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.)

video shot boundary detection

need source code for matlab

"1D FDTD solution for open boundary in a unitless domain with a Courant factor > 1 (Unstable solutions leading to blow-up)"