This sample program generates two sine waves called X and Y. It will then calculate the normalized magnitude and phase of the two waveforms using the following formulas: Mag = sqrt(X^2 + Y^2)/sqrt(GainX^2 + GainY^2) Phase = (long) (atan2PU(X,Y) * 360) The program will prompt the user to change the gain and frequency of the X and Y waveforms.
标签： Y. normalized generates calculate
上传时间： 2014-01-05
上传用户：123456wh
This a GA implementation using binary and real coded variables. Mixed variables can be used. Constraints can also be handled. All constraints must be greater-than-equal-to type (g >= 0) and normalized (see the sample problem in prob1 in objective()).
标签： variables implementation Constra binary
上传时间： 2015-03-15
上传用户：qiao8960
基于Volterra滤波器混沌时间序列多步预测 作者：陆振波，海军工程大学 欢迎同行来信交流与合作，更多文章与程序下载请访问我的个人主页 电子邮件：luzhenbo@sina.com 个人主页：luzhenbo.88uu.com.cn 参考文献： 1、张家树.混沌时间序列的Volterra自适应预测.物理学报.2000.03 2、Scott C.Douglas, Teresa H.-Y. Meng, normalized Data Nonlinearities for LMS Adaptation. IEEE Trans.Sign.Proc. Vol.42 1994 文件说明： 1、original_MultiStepPred_main.m 程序主文件,直接运行此文件即可 2、original_train.m 训练函数 3、original_test.m 测试函数 4、LorenzData.dll 产生Lorenz离散序列 5、normalize_1.m 归一化 6、PhaSpaRecon.m 相空间重构 7、PhaSpa2VoltCoef.dll 构造 Volterra 自适应 FIR 滤波器的输入信号矢量 Un 8、TrainTestSample_2.m 将特征矩阵前 train_num 个为训练样本，其余为测试样本 9、FIR_NLMS.dll NLMS自适应算法
上传时间： 2013-12-16
上传用户：talenthn
一种 较新的聚类算法 Dominant-set 的代码，包括聚类算法的代码和测试代码。该算法最大特点 就是基于图理论的 ，相对于normalized Cut,计算复杂度低很多，况且能自动决定类的个数
标签： Dominant-set 聚类算法 代码
上传时间： 2013-12-19
上传用户：417313137
iris localization using integro differential operator. The rar contains 5 files in order to computer the integro differential operator of the normalized contour of the iris and puil boundaries and then add circles to the respective boundaries.
标签： differential localization contains computer
上传时间： 2017-03-23
上传用户：希酱大魔王
The existence of numerous imaging modalities makes it possible to present different data present in different modalities together thus forming multimodal images. Component images forming multimodal images should be aligned, or registered so that all the data, coming from the different modalities, are displayed in proper locations. The term image registration is most commonly used to denote the process of alignment of images , that is of transforming them to the common coordinate system. This is done by optimizing a similarity measure between the two images. A widely used measure is Mutual Information (MI). This method requires estimating joint histogram of the two images. Experiments are presented that demonstrate the approach. The technique is intensity-based rather than feature-based. As a comparative assessment the performance based on normalized mutual information and cross correlation as metric have also been presented.
标签： present modalities existence different
上传时间： 2017-04-02
上传用户：qunquan
Computes all eigenvalues and eigenvectors of a real symmetric matrix a, ! which is of size n by n, stored in a physical np by np array. ! On output, elements of a above the diagonal are destroyed. ! d returns the eigenvalues of a in its first n elements. ! v is a matrix with the same logical and physical dimensions as a, ! whose columns contain, on output, the normalized eigenvectors of a. ! nrot returns the number of Jacobi rotations that were required. ! Please notice that the eigenvalues are not ordered on output. ! If the sorting is desired, the addintioal routine "eigsrt" ! can be invoked to reorder the output of jacobi.
上传时间： 2016-06-04
上传用户：1512313
We are currently witnessing an increase in telecommunications norms and standards given the recent advances in this domain. The increasing number of normalized standards paves the way for an increase in the range of offers and services available for each consumer. Moreover, the majority of available radio frequencies have already been allocated.
标签： Allocation Resource Radio
上传时间： 2020-05-31
上传用户：shancjb
