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CLAHE: contrast limited adaptive histogram equalization is one of the most famous algorithm in image enhancement

Optimal Power Flow algorithm

Stephen J.Chapman 著 邢树军等译 国外高校电子信息类优秀教材，与大家分享下！尤其适合初学者. (Stephen J.Chapman )

比例导引法的几个matlab程序，根据绝对弹道进行编程设计(Proportional navigation law matlab program, according to the absolute ballistic Programming)

说明：  该算法可以实现基本的萤火虫求解，还有其他萤火虫集合，以及和其他算法的融合(The algorithm can realize basic firefly solution, other firefly sets and fusion with other algorithms)

混沌模糊算法函数，调用此函数可以解决许多初学者的疑惑(Chaotic fuzzy arithmetic functions, calling this function can solve many doubts beginners)

应用matlab_simulink搭建模块进行电路仿真，欢迎大家学习！！(matlab_simulink)

Employee management system project for students.

本文提出的中值滤波的快速算法的基本思想是：原始数据序列上中值滤波的滑窗在移动过程中，当前窗只要删除其最早的元素，加入窗后的新元素，即成为下一窗的内容。这个只是Matlab里封装的算法代码(In this paper, the median filtering of the fast algorithm for the basic idea is: the original data sequence in the sliding window filtering process in the mobile, the current window as long as the deletion of its first element, adding a new element after the window, that is, the next window content.)

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.)