cancer

多目标优化 相对传统多目标优化方法, PSO在求解多目标问题上具有很大优势。首先, PSO的高效搜索能力有利于得到多目标意义下的最优解 其次, PSO通过代表整个解集的种群按内在的并行方式同时搜索多个非劣解,因此容易搜索到多个Pareto 最优解 再则, PSO的通用性使其适合于处理所有类型的目标函数和约束 另外, PSO 很容易与传统方法相结合,进而提出解决特定问题的高效方法。就PSO 本身而言,为了更好地解决多目标优化问题,必须解决全局最优粒子和个体最优粒子的选择问题(Compared with the traditional multi-objective optimization of multi-objective optimization method, PSO in solving multi-objective problem has a great advantage. First, PSO is conducive to the efficient search capabilities are more objective sense of the optimal solution Secondly, PSO representative of the entire solution set through the population by way of the inherent parallel search multiple non-inferior solution, and this can easily search for the most number of Pareto optimal solution Furthermore, PSO' s versatility make it suitable for handling all types of objective function and constraints addition, PSO is easy to integrate with the traditional method, and then propose an efficient way to solve specific problems. The PSO itself, in order to better address the multi-objective optimization problems, the need to address the global best particle and the individual selection of the optimal particle)

求单变量反馈控制回路的输出时间延迟 X为闭环回路输出时间序列 寻找时间延迟tau：即Sdeltmean第一个极小值点对应的t(Find a single variable feedback control loop time delay the output of X is closed-loop output time series to find the time delay tau: the Sdeltmean the first minimum point corresponding to t)

卡尔曼滤波程序，卡尔曼滤波程序，卡尔曼滤波程序，(Kalman filtering procedures, Kalman filtering procedures, Kalman filtering procedures,)

本文首先概述了预编码技术的发展历史、基本原理和研究意义。重点介绍了预编码技术在LTE及LTE-A系统中的应用，最后对预编码技术的发展趋势做出预测及综合评论。(This paper outlines the history of pre-coding technology, the basic principles and significance. Focuses on the pre-coding technology in LTE and LTE-A system, and finally to make predictions and comprehensive review on the development trend of the pre-coding technology.)

说明：  AR一阶算法，可利用AR（1）进行数据预测和随机序列处理(AR First Order Algorithms)

Genetic algorithm for optimization

说明：  用C-C时间序列插入构造李亚普诺夫计算方法(Time series with CC Insert method of calculating Lyapunov structure)

K均值（用matlab实现花的分类，附注释，程序简单）(K-means (machine learning job classification flowers))

Under the assumption of absolutely no deterministic knowledge about the signal X(n), i.e., we assume that we know only the average power in the signal. In this case the optimal detector is energy detector or radiometer can be represented as [23]

无线传感器网络定位技术的matlab算法合集，不包含蒙特卡罗方法(A set of MATLAB algorithms for wireless sensor network location technology without Monte Carlo method)