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Synopsys® Timing Constraints and Optimization User Guide

mann-kendall趋势性检验，用于检验一组数据趋势性情况(mann-kendall trend test, a set of data used to test the trend of the situation)

Cart-pole problem solition with python

image retrieval using L2 distance:euclidien distance between 2 histograms

多频道奇异谱分析，即奇异谱分析的升级版，广泛应用于气象变化，股市波动，降噪等领域。(Multi-channel singular spectrum analysis, that singular spectrum analysis of an upgraded version of the widely used weather changes, stock market volatility, noise reduction and other areas.)

说明：  使用时打开此例题目录下pic中的图片，然后依次单击按钮“转”、“1”、“2”、“3”、“4”和“5”，就可以实现精确的车牌定位。(use this example to open directory pic of pictures, then click the button "turn", "1", "2", "3" and "4" and "5", can achieve precise positioning of the plates.)

Matlab中几个数值积分函数的比较和优缺点介绍

二维圆柱形光子晶体波导TE波MATLAB仿真(Two-dimensional cylindrical photonic crystal waveguide TE wave simulation)

感知器感知器算法训练二元线性分类器。结构体数据使用感知器学习规则 找到给定的二分类标签数据超平面。 (PERCEPTRON Perceptron algorithm to train binary linear classifier. Synopsis: model = perceptron(data) model = perceptron(data,options) model = perceptron(data,options,init_model) Description: model = perceptron(data) uses the Perceptron learning rule to find separating hyperplane from given binary labeled data. model = perceptron(data,options) specifies stopping condition of the algorithm in structure options: .tmax [1x1]... maximal number of iterations. If tmax==-1 then it only returns index (model.last_update) of data vector which should be used by the algorithm for updating the linear rule in the next iteration. model = perceptron(data,options,init_model) specifies initial model which must contain: .W [dim x 1] ... normal vector. .b [1x1] ... bias of hyperplane. .t [1x1] (optional) ... iteration number. Input: data [struct] Labeled (binary) training data. .X [dim x num)

产生两个远程的发送信号,采用归一化处理使其中一个信号有时延,然后求两个接收信号的高阶累积量.(have two long-distance signal transmission, is used to make a treatment in which a signal delay, Then the received signal for the two Cumulant.)