Reactive-power-compensation

偏最小二乘（PLS）算法建模，并提供一个实例分析，提供异常过程监控Q统计量和T统计量。检测出故障。(Partial Least Squares (PLS) algorithm modeling, and provides a case study to provide process monitoring abnormal Q statistic and T statistics. To detect the fault.)

Keller box algorithm and equations for Boundary layer theory problems. For calculating the boundary layer thickness and the velocity profile in a free stream in a pipe.

论文<Outage Probability of Multihop Transmission Over Nakagami Fading Channels>文章的matlab仿真程序 ，作者mazen(Thesis <Outage Probability of Multihop Transmission Over Nakagami Fading Channels> Article matlab simulation program, the authors mazen)

说明：  This guide explain s function for matlab simulink

这个程序可用来画R(D)函数，学习信息论的一般要做这个。(This procedure can be used to draw R (D) function, learning the general information theory to do this.)

采用多天线的认知无线电系统相对于单天线认知无线电系统，既有传统的资源（频域，时域，码域），又有空域资源。本文研究基于博弈论的有限反馈认知MIMO系统的资源分配，涉及发射功率、空域（采用波束成形）和反馈速率等资源的分配。利用有限的反馈信道反馈量化的信道状态信息(CSI)，基于量化CSI，本文主要研究联合功率分配与波束成形优化、次用户（认知用户或非授权用户）反馈速率控制、联合功率分配与反馈速率控制等相关资源分配问题。(Multi-antenna cognitive radio system with respect to a single antenna cognitive radio systems, both traditional resource (frequency domain, time domain, code domain), there airspace resources. In this paper, a limited resource allocation game theory of cognitive MIMO system based on feedback, involving the launch distribution power, airspace (using beam-forming) and feedback rate and other resources. With limited feedback channel feedback quantized channel state information (CSI), based on quantified CSI, this paper studies the joint power allocation and beamforming optimization, secondary users (cognitive user or unauthorized user) feedback rate control, joint power allocation and feedback rate control and other issues related to resource allocation.)

Time series RBF predict

卫星移动通信系统的电子教材，解压后可见，研究学习卫星通信的人可以参考借鉴(Electronic textbooks satellite mobile communication system, unpacked visible satellite communications research study can be a reference for people)

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)

very simple watermarking using matlab. to hide a message in cover image..