power-allocatin

matlab在子集和问题上的应用，与遗传算法的结合使用(matlab subset problem, with the combined use of the genetic algorithm)

amplitude sjift keyingg

Q-learning (Watkins, 1989) is a simple way for agents to learn how to act optimally in controlled Markovian domains. It amounts to an incremental method for dynamic programming which imposes limited computational demands. It works by successively improving its evaluations of the quality of particular actions at particular states. This paper presents and proves in detail a convergence theorem for Q,-learning based on that outlined in Watkins (1989). We show that Q-learning converges to the optimum action-values with probability 1 so long as all actions are repeatedly sampled in all states and the action-values are represented discretely. We also sketch extensions to the cases of non-discounted, but absorbing, Markov environments, and where many Q values can be changed each iteration, rather than just one.

Non Convex Algorithms for Group Sparse Optimization by Angshul Majumdar @matlab central (Non Convex Algorithms for Group Sparse Optimization by Angshul Majumdar @matlab central)

Hi ,it s a simple code

engineering statistic

一个反应非线性电弧炉元件电压电流特性的MATLAB程序(A reaction the nonlinear arc furnace components of voltage and current characteristics of the MATLAB program)

边缘检测对于图像理解、目标检测、跟踪等问题非常重要，该代码实现了canny算子做边缘检测(Edge detection for image understanding, target detection, tracking a very important issue, the code implementation of the canny edge detection operator to do)

用于自适应盲均衡的自适应变模SCA算法,具有良好的性能.(Adaptive blind equalization for Adaptive Variable modulus SCA algorithm has good performance.)

说明：  F分布的参数 随机数样本数量 随机数样本产生(F distribution parameters of random samples of a few number of samples generated random number)