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系统辨识的最小二乘递推算法、辅助变量法、增广最小二乘法及偏差补偿法的matlab程序设计实例。(Recursive least squares system identification algorithm, auxiliary variables, the least square method and the augmented error compensation law matlab programming examples.)

说明：  lms算法的仿真和yule_walker方程的仿真。这两种算法都是随机信号处理的有效方法。(lms algorithm yule_walker of the simulation and the simulation equations. These two algorithms are effective random signal processing methods.)

说明：  基于遗传算法的matlab求解VRP问题（包含时间窗限制）(Genetic algorithm for VRP)

Minimum shift keying modulation

这是规则化滤波复原的matlab代码，需要的可以作为参考(This is the matlab code regularization filter recovery, need can be used as a reference)

一个身体部位比较模型的新方法网络（BAN）的，可以容纳多个环节和多个科目。所述的绝对测量允许跨频谱可能刻画的比较 从单参数为整个合奏，通过基于参数化到每个活动，每个学科和每个环节模型。使用错误，并明确之间权衡复杂性，在一个善良的适应措施相结合，显示有重要的影响时，适用于一系列典型的禁止通道数据。它是有不同的 在模式的选择的影响，以及它相关的复杂性，混合活动的“日常”的数据，设置活动相比，动态数据（例如步行）。平均路径损耗的不足，甚至位数的路径损失的措施，作为唯一的表征还强调“禁止通道。 (A new approach to compare models for body area networks (BAN) that accommodates multiple links and multiple subjects is presented. The absolute measure described allows comparison across a spectrum of possible characterizations ranging from single-parameter for an entire ensemble, through to per-activity, per-subject and per-link based parameterized models. The use of an explicit trade-off between error and complexity, combined in a goodness-of-fit measure, is shown to have important consequences when applied to a range of typical BAN channel data. It is shown that there are different implications in choice of model, and it’s associated complexity, for mixed-activity “everyday” data, when compared with set-activity dynamic data (e.g. walking). The deficiency of mean path loss, or even median path loss measures, as a sole characterization of the BAN channel is also highlighted.)

互信息相关的一些资料和代码，比较有借鉴意义的，大家可以看一下(Mutual information related to some of the information, more reference, we can look at)

多目标蝗虫优化算法源代码,benchmark函数优化，测试效果好。(Multi-objective Grasshopper Optimization Algorithm (MOGOA) source codes)

很好的FEM（有限元）matlab工具包(good FEM (Finite Element) Matlab Kit)

说明：  本文从ARQ协议出发，建立了基于离散时间的GEOM/G/1排队模型。(This departure from the ARQ protocol, based on a discrete time queuing model GEOM/G/1.)