登录
首页 » matlab » sparse-coprime-

sparse-coprime-

于 2020-07-10 发布
0 226
下载积分: 1 下载次数: 40

代码说明:

说明:  sparse coprime array direction of arrival

文件列表:

sparse-coprime-sensor-arrays-60ec3c9a1c2219ddfc896883c09933df546eb865, 0 , 2019-03-30
sparse-coprime-sensor-arrays-60ec3c9a1c2219ddfc896883c09933df546eb865\3rd party functions, 0 , 2019-03-30
sparse-coprime-sensor-arrays-60ec3c9a1c2219ddfc896883c09933df546eb865\3rd party functions\BeampatternLinearArray.m, 1562 , 2019-03-30
sparse-coprime-sensor-arrays-60ec3c9a1c2219ddfc896883c09933df546eb865\3rd party functions\CoprimeArrayAnalysis.m, 4383 , 2019-03-30
sparse-coprime-sensor-arrays-60ec3c9a1c2219ddfc896883c09933df546eb865\3rd party functions\FullArrayAnalysis.m, 3046 , 2019-03-30
sparse-coprime-sensor-arrays-60ec3c9a1c2219ddfc896883c09933df546eb865\3rd party functions\NestedArrayAnalysis.m, 4376 , 2019-03-30
sparse-coprime-sensor-arrays-60ec3c9a1c2219ddfc896883c09933df546eb865\3rd party functions\ProdMinMUSIC.m, 5084 , 2019-03-30
sparse-coprime-sensor-arrays-60ec3c9a1c2219ddfc896883c09933df546eb865\3rd party functions\ProductMinBeampattern.m, 1955 , 2019-03-30
sparse-coprime-sensor-arrays-60ec3c9a1c2219ddfc896883c09933df546eb865\3rd party functions\RUNtemporalFT.m, 71 , 2019-03-30
sparse-coprime-sensor-arrays-60ec3c9a1c2219ddfc896883c09933df546eb865\3rd party functions\coarrayTotal.m, 1243 , 2019-03-30
sparse-coprime-sensor-arrays-60ec3c9a1c2219ddfc896883c09933df546eb865\3rd party functions\directionEstimates.m, 10539 , 2019-03-30
sparse-coprime-sensor-arrays-60ec3c9a1c2219ddfc896883c09933df546eb865\3rd party functions\ifourierTrans.m, 473 , 2019-03-30
sparse-coprime-sensor-arrays-60ec3c9a1c2219ddfc896883c09933df546eb865\3rd party functions\temporalFT.m, 897 , 2019-03-30
sparse-coprime-sensor-arrays-60ec3c9a1c2219ddfc896883c09933df546eb865\README.md, 1459 , 2019-03-30
sparse-coprime-sensor-arrays-60ec3c9a1c2219ddfc896883c09933df546eb865\results, 0 , 2019-03-30
sparse-coprime-sensor-arrays-60ec3c9a1c2219ddfc896883c09933df546eb865\results\min_prod_analysis, 0 , 2019-03-30
sparse-coprime-sensor-arrays-60ec3c9a1c2219ddfc896883c09933df546eb865\results\min_prod_analysis\00001_res_, 0 , 2019-03-30
sparse-coprime-sensor-arrays-60ec3c9a1c2219ddfc896883c09933df546eb865\results\min_prod_analysis\00001_res_\Figures, 0 , 2019-03-30
sparse-coprime-sensor-arrays-60ec3c9a1c2219ddfc896883c09933df546eb865\results\min_prod_analysis\00001_res_\Figures\Minimum, 0 , 2019-03-30
sparse-coprime-sensor-arrays-60ec3c9a1c2219ddfc896883c09933df546eb865\results\min_prod_analysis\00001_res_\Figures\Minimum\2_100_1.fig, 56518 , 2019-03-30
sparse-coprime-sensor-arrays-60ec3c9a1c2219ddfc896883c09933df546eb865\results\min_prod_analysis\00001_res_\Figures\Minimum\2_100_10.fig, 28893 , 2019-03-30
sparse-coprime-sensor-arrays-60ec3c9a1c2219ddfc896883c09933df546eb865\results\min_prod_analysis\00001_res_\Figures\Minimum\2_100_11.fig, 48801 , 2019-03-30
sparse-coprime-sensor-arrays-60ec3c9a1c2219ddfc896883c09933df546eb865\results\min_prod_analysis\00001_res_\Figures\Minimum\2_100_12.fig, 24647 , 2019-03-30
sparse-coprime-sensor-arrays-60ec3c9a1c2219ddfc896883c09933df546eb865\results\min_prod_analysis\00001_res_\Figures\Minimum\2_100_13.fig, 48523 , 2019-03-30
sparse-coprime-sensor-arrays-60ec3c9a1c2219ddfc896883c09933df546eb865\results\min_prod_analysis\00001_res_\Figures\Minimum\2_100_14.fig, 29224 , 2019-03-30
sparse-coprime-sensor-arrays-60ec3c9a1c2219ddfc896883c09933df546eb865\results\min_prod_analysis\00001_res_\Figures\Minimum\2_100_15.fig, 32900 , 2019-03-30
sparse-coprime-sensor-arrays-60ec3c9a1c2219ddfc896883c09933df546eb865\results\min_prod_analysis\00001_res_\Figures\Minimum\2_100_16.fig, 31578 , 2019-03-30
sparse-coprime-sensor-arrays-60ec3c9a1c2219ddfc896883c09933df546eb865\results\min_prod_analysis\00001_res_\Figures\Minimum\2_100_17.fig, 47908 , 2019-03-30
sparse-coprime-sensor-arrays-60ec3c9a1c2219ddfc896883c09933df546eb865\results\min_prod_analysis\00001_res_\Figures\Minimum\2_100_18.fig, 23423 , 2019-03-30
sparse-coprime-sensor-arrays-60ec3c9a1c2219ddfc896883c09933df546eb865\results\min_prod_analysis\00001_res_\Figures\Minimum\2_100_19.fig, 47082 , 2019-03-30
sparse-coprime-sensor-arrays-60ec3c9a1c2219ddfc896883c09933df546eb865\results\min_prod_analysis\00001_res_\Figures\Minimum\2_100_2.fig, 34709 , 2019-03-30
sparse-coprime-sensor-arrays-60ec3c9a1c2219ddfc896883c09933df546eb865\results\min_prod_analysis\00001_res_\Figures\Minimum\2_100_3.fig, 41694 , 2019-03-30
sparse-coprime-sensor-arrays-60ec3c9a1c2219ddfc896883c09933df546eb865\results\min_prod_analysis\00001_res_\Figures\Minimum\2_100_4.fig, 34399 , 2019-03-30
sparse-coprime-sensor-arrays-60ec3c9a1c2219ddfc896883c09933df546eb865\results\min_prod_analysis\00001_res_\Figures\Minimum\2_100_5.fig, 46905 , 2019-03-30
sparse-coprime-sensor-arrays-60ec3c9a1c2219ddfc896883c09933df546eb865\results\min_prod_analysis\00001_res_\Figures\Minimum\2_100_6.fig, 25967 , 2019-03-30
sparse-coprime-sensor-arrays-60ec3c9a1c2219ddfc896883c09933df546eb865\results\min_prod_analysis\00001_res_\Figures\Minimum\2_100_7.fig, 48469 , 2019-03-30
sparse-coprime-sensor-arrays-60ec3c9a1c2219ddfc896883c09933df546eb865\results\min_prod_analysis\00001_res_\Figures\Minimum\2_100_8.fig, 33445 , 2019-03-30
sparse-coprime-sensor-arrays-60ec3c9a1c2219ddfc896883c09933df546eb865\results\min_prod_analysis\00001_res_\Figures\Minimum\2_100_9.fig, 39791 , 2019-03-30
sparse-coprime-sensor-arrays-60ec3c9a1c2219ddfc896883c09933df546eb865\results\min_prod_analysis\00001_res_\Figures\Product, 0 , 2019-03-30
sparse-coprime-sensor-arrays-60ec3c9a1c2219ddfc896883c09933df546eb865\results\min_prod_analysis\00001_res_\Figures\Product\2_100_1.fig, 57178 , 2019-03-30
sparse-coprime-sensor-arrays-60ec3c9a1c2219ddfc896883c09933df546eb865\results\min_prod_analysis\00001_res_\Figures\Product\2_100_10.fig, 29385 , 2019-03-30
sparse-coprime-sensor-arrays-60ec3c9a1c2219ddfc896883c09933df546eb865\results\min_prod_analysis\00001_res_\Figures\Product\2_100_11.fig, 49454 , 2019-03-30
sparse-coprime-sensor-arrays-60ec3c9a1c2219ddfc896883c09933df546eb865\results\min_prod_analysis\00001_res_\Figures\Product\2_100_12.fig, 24988 , 2019-03-30
sparse-coprime-sensor-arrays-60ec3c9a1c2219ddfc896883c09933df546eb865\results\min_prod_analysis\00001_res_\Figures\Product\2_100_13.fig, 49380 , 2019-03-30
sparse-coprime-sensor-arrays-60ec3c9a1c2219ddfc896883c09933df546eb865\results\min_prod_analysis\00001_res_\Figures\Product\2_100_14.fig, 29694 , 2019-03-30
sparse-coprime-sensor-arrays-60ec3c9a1c2219ddfc896883c09933df546eb865\results\min_prod_analysis\00001_res_\Figures\Product\2_100_15.fig, 33349 , 2019-03-30
sparse-coprime-sensor-arrays-60ec3c9a1c2219ddfc896883c09933df546eb865\results\min_prod_analysis\00001_res_\Figures\Product\2_100_16.fig, 32116 , 2019-03-30
sparse-coprime-sensor-arrays-60ec3c9a1c2219ddfc896883c09933df546eb865\results\min_prod_analysis\00001_res_\Figures\Product\2_100_17.fig, 48806 , 2019-03-30
sparse-coprime-sensor-arrays-60ec3c9a1c2219ddfc896883c09933df546eb865\results\min_prod_analysis\00001_res_\Figures\Product\2_100_18.fig, 23652 , 2019-03-30
sparse-coprime-sensor-arrays-60ec3c9a1c2219ddfc896883c09933df546eb865\results\min_prod_analysis\00001_res_\Figures\Product\2_100_19.fig, 48050 , 2019-03-30
sparse-coprime-sensor-arrays-60ec3c9a1c2219ddfc896883c09933df546eb865\results\min_prod_analysis\00001_res_\Figures\Product\2_100_2.fig, 35145 , 2019-03-30
sparse-coprime-sensor-arrays-60ec3c9a1c2219ddfc896883c09933df546eb865\results\min_prod_analysis\00001_res_\Figures\Product\2_100_3.fig, 42341 , 2019-03-30
sparse-coprime-sensor-arrays-60ec3c9a1c2219ddfc896883c09933df546eb865\results\min_prod_analysis\00001_res_\Figures\Product\2_100_4.fig, 34879 , 2019-03-30
sparse-coprime-sensor-arrays-60ec3c9a1c2219ddfc896883c09933df546eb865\results\min_prod_analysis\00001_res_\Figures\Product\2_100_5.fig, 47584 , 2019-03-30
sparse-coprime-sensor-arrays-60ec3c9a1c2219ddfc896883c09933df546eb865\results\min_prod_analysis\00001_res_\Figures\Product\2_100_6.fig, 26247 , 2019-03-30
sparse-coprime-sensor-arrays-60ec3c9a1c2219ddfc896883c09933df546eb865\results\min_prod_analysis\00001_res_\Figures\Product\2_100_7.fig, 49136 , 2019-03-30
sparse-coprime-sensor-arrays-60ec3c9a1c2219ddfc896883c09933df546eb865\results\min_prod_analysis\00001_res_\Figures\Product\2_100_8.fig, 33852 , 2019-03-30
sparse-coprime-sensor-arrays-60ec3c9a1c2219ddfc896883c09933df546eb865\results\min_prod_analysis\00001_res_\Figures\Product\2_100_9.fig, 40438 , 2019-03-30
sparse-coprime-sensor-arrays-60ec3c9a1c2219ddfc896883c09933df546eb865\results\min_prod_analysis\00001_res_\Minimum, 0 , 2019-03-30
sparse-coprime-sensor-arrays-60ec3c9a1c2219ddfc896883c09933df546eb865\results\min_prod_analysis\00001_res_\Minimum\2_100_1.mat, 16835 , 2019-03-30
sparse-coprime-sensor-arrays-60ec3c9a1c2219ddfc896883c09933df546eb865\results\min_prod_analysis\00001_res_\Minimum\2_100_10.mat, 6884 , 2019-03-30
sparse-coprime-sensor-arrays-60ec3c9a1c2219ddfc896883c09933df546eb865\results\min_prod_analysis\00001_res_\Minimum\2_100_11.mat, 13839 , 2019-03-30
sparse-coprime-sensor-arrays-60ec3c9a1c2219ddfc896883c09933df546eb865\results\min_prod_analysis\00001_res_\Minimum\2_100_12.mat, 5704 , 2019-03-30
sparse-coprime-sensor-arrays-60ec3c9a1c2219ddfc896883c09933df546eb865\results\min_prod_analysis\00001_res_\Minimum\2_100_13.mat, 13806 , 2019-03-30
sparse-coprime-sensor-arrays-60ec3c9a1c2219ddfc896883c09933df546eb865\results\min_prod_analysis\00001_res_\Minimum\2_100_14.mat, 7052 , 2019-03-30
sparse-coprime-sensor-arrays-60ec3c9a1c2219ddfc896883c09933df546eb865\results\min_prod_analysis\00001_res_\Minimum\2_100_15.mat, 8254 , 2019-03-30
sparse-coprime-sensor-arrays-60ec3c9a1c2219ddfc896883c09933df546eb865\results\min_prod_analysis\00001_res_\Minimum\2_100_16.mat, 7790 , 2019-03-30
sparse-coprime-sensor-arrays-60ec3c9a1c2219ddfc896883c09933df546eb865\results\min_prod_analysis\00001_res_\Minimum\2_100_17.mat, 13467 , 2019-03-30
sparse-coprime-sensor-arrays-60ec3c9a1c2219ddfc896883c09933df546eb865\results\min_prod_analysis\00001_res_\Minimum\2_100_18.mat, 5374 , 2019-03-30
sparse-coprime-sensor-arrays-60ec3c9a1c2219ddfc896883c09933df546eb865\results\min_prod_analysis\00001_res_\Minimum\2_100_19.mat, 13153 , 2019-03-30
sparse-coprime-sensor-arrays-60ec3c9a1c2219ddfc896883c09933df546eb865\results\min_prod_analysis\00001_res_\Minimum\2_100_2.mat, 8931 , 2019-03-30
sparse-coprime-sensor-arrays-60ec3c9a1c2219ddfc896883c09933df546eb865\results\min_prod_analysis\00001_res_\Minimum\2_100_3.mat, 11431 , 2019-03-30
sparse-coprime-sensor-arrays-60ec3c9a1c2219ddfc896883c09933df546eb865\results\min_prod_analysis\00001_res_\Minimum\2_100_4.mat, 8762 , 2019-03-30
sparse-coprime-sensor-arrays-60ec3c9a1c2219ddfc896883c09933df546eb865\results\min_prod_analysis\00001_res_\Minimum\2_100_5.mat, 13074 , 2019-03-30
sparse-coprime-sensor-arrays-60ec3c9a1c2219ddfc896883c09933df546eb865\results\min_prod_analysis\00001_res_\Minimum\2_100_6.mat, 6080 , 2019-03-30
sparse-coprime-sensor-arrays-60ec3c9a1c2219ddfc896883c09933df546eb865\results\min_prod_analysis\00001_res_\Minimum\2_100_7.mat, 13670 , 2019-03-30
sparse-coprime-sensor-arrays-60ec3c9a1c2219ddfc896883c09933df546eb865\results\min_prod_analysis\00001_res_\Minimum\2_100_8.mat, 8458 , 2019-03-30
sparse-coprime-sensor-arrays-60ec3c9a1c2219ddfc896883c09933df546eb865\results\min_prod_analysis\00001_res_\Minimum\2_100_9.mat, 10761 , 2019-03-30
sparse-coprime-sensor-arrays-60ec3c9a1c2219ddfc896883c09933df546eb865\results\min_prod_analysis\00001_res_\Product, 0 , 2019-03-30
sparse-coprime-sensor-arrays-60ec3c9a1c2219ddfc896883c09933df546eb865\results\min_prod_analysis\00001_res_\Product\2_100_1.mat, 17046 , 2019-03-30
sparse-coprime-sensor-arrays-60ec3c9a1c2219ddfc896883c09933df546eb865\results\min_prod_analysis\00001_res_\Product\2_100_10.mat, 7007 , 2019-03-30
sparse-coprime-sensor-arrays-60ec3c9a1c2219ddfc896883c09933df546eb865\results\min_prod_analysis\00001_res_\Product\2_100_11.mat, 14003 , 2019-03-30
sparse-coprime-sensor-arrays-60ec3c9a1c2219ddfc896883c09933df546eb865\results\min_prod_analysis\00001_res_\Product\2_100_12.mat, 5804 , 2019-03-30
sparse-coprime-sensor-arrays-60ec3c9a1c2219ddfc896883c09933df546eb865\results\min_prod_analysis\00001_res_\Product\2_100_13.mat, 14024 , 2019-03-30
sparse-coprime-sensor-arrays-60ec3c9a1c2219ddfc896883c09933df546eb865\results\min_prod_analysis\00001_res_\Product\2_100_14.mat, 7165 , 2019-03-30
sparse-coprime-sensor-arrays-60ec3c9a1c2219ddfc896883c09933df546eb865\results\min_prod_analysis\00001_res_\Product\2_100_15.mat, 8383 , 2019-03-30
sparse-coprime-sensor-arrays-60ec3c9a1c2219ddfc896883c09933df546eb865\results\min_prod_analysis\00001_res_\Product\2_100_16.mat, 7958 , 2019-03-30
sparse-coprime-sensor-arrays-60ec3c9a1c2219ddfc896883c09933df546eb865\results\min_prod_analysis\00001_res_\Product\2_100_17.mat, 13741 , 2019-03-30
sparse-coprime-sensor-arrays-60ec3c9a1c2219ddfc896883c09933df546eb865\results\min_prod_analysis\00001_res_\Product\2_100_18.mat, 5475 , 2019-03-30
sparse-coprime-sensor-arrays-60ec3c9a1c2219ddfc896883c09933df546eb865\results\min_prod_analysis\00001_res_\Product\2_100_19.mat, 13429 , 2019-03-30
sparse-coprime-sensor-arrays-60ec3c9a1c2219ddfc896883c09933df546eb865\results\min_prod_analysis\00001_res_\Product\2_100_2.mat, 9053 , 2019-03-30
sparse-coprime-sensor-arrays-60ec3c9a1c2219ddfc896883c09933df546eb865\results\min_prod_analysis\00001_res_\Product\2_100_3.mat, 11548 , 2019-03-30
sparse-coprime-sensor-arrays-60ec3c9a1c2219ddfc896883c09933df546eb865\results\min_prod_analysis\00001_res_\Product\2_100_4.mat, 8888 , 2019-03-30
sparse-coprime-sensor-arrays-60ec3c9a1c2219ddfc896883c09933df546eb865\results\min_prod_analysis\00001_res_\Product\2_100_5.mat, 13240 , 2019-03-30
sparse-coprime-sensor-arrays-60ec3c9a1c2219ddfc896883c09933df546eb865\results\min_prod_analysis\00001_res_\Product\2_100_6.mat, 6149 , 2019-03-30
sparse-coprime-sensor-arrays-60ec3c9a1c2219ddfc896883c09933df546eb865\results\min_prod_analysis\00001_res_\Product\2_100_7.mat, 13871 , 2019-03-30
sparse-coprime-sensor-arrays-60ec3c9a1c2219ddfc896883c09933df546eb865\results\min_prod_analysis\00001_res_\Product\2_100_8.mat, 8577 , 2019-03-30
sparse-coprime-sensor-arrays-60ec3c9a1c2219ddfc896883c09933df546eb865\results\min_prod_analysis\00001_res_\Product\2_100_9.mat, 10942 , 2019-03-30
sparse-coprime-sensor-arrays-60ec3c9a1c2219ddfc896883c09933df546eb865\results\min_prod_analysis\Old_tables, 0 , 2019-03-30
sparse-coprime-sensor-arrays-60ec3c9a1c2219ddfc896883c09933df546eb865\results\min_prod_analysis\Old_tables\00001_res, 0 , 2019-03-30

下载说明:请别用迅雷下载,失败请重下,重下不扣分!

发表评论

0 个回复

  • filter_s
    Generates the filtered BPSK and plots the spectrum
    2009-09-23 10:07:12下载
    积分:1
  • matlab-uniquac
    本程序使用matlab语言,编制了一个基于通用似化学活度系数模型来计算四组分反应体系中各组分的汽液平衡状态的程序.(This procedure using the matlab language, developed a chemical based on a common activity coefficient model seems to calculate the four-component reaction system of the components of the vapor-liquid equilibrium of the program.)
    2020-08-30 20:48:10下载
    积分:1
  • MMUSIC
    利用经典MUSIC算法及MMUSIC算法估计波达方向,绝对可运行!程序没错误!(Using the classical MUSIC algorithm and MMUSIC algorithm to estimate DOA, absolutely can run! Program did not wrong!)
    2021-04-28 17:08:43下载
    积分:1
  • Genetic.P
    遗传算法的书籍,适合初学者快速上手学习用。(Genetic Algorithm books)
    2013-12-27 15:51:49下载
    积分:1
  • penhao
    分析了该信号的时域、频域、倒谱,循环谱等,在matlab R2009b调试通过,光纤陀螺输出误差的allan方差分析。( Analysis of the signal time domain, frequency domain, cepstrum, cyclic spectrum, etc. In matlab R2009b debugging through, allan FOG output error variance analysis.)
    2016-05-10 14:48:57下载
    积分:1
  • Optimizationproblem
    matlab最优化问题整理,对matlab常用的一些最优化函数做了介绍(matlab optimization problem finishing, some of the most commonly used on the matlab optimization function, made an introductory)
    2010-02-27 11:17:47下载
    积分:1
  • MATLAB
    简单叙述了M月TLAB语言的特点,并介绍了如何用材月了乙AB语言编写程序,实现示 波器和频语仪的仿真。 (Brief description of the M language features on TLAB, and describes how to use the materials on the B programming language AB, scope and frequency of language instrument to achieve the simulation.)
    2011-08-07 14:46:40下载
    积分:1
  • libsvm-pattern-classification
    matlab平台下libsvm程序包进行模式分类(libsvm in matlab to pattern classification)
    2013-03-16 23:49:21下载
    积分:1
  • ADC_Streamer
    ADC streamer matlab code and gui
    2012-02-13 17:17:06下载
    积分:1
  • 灰狼优化
    以优化SVM算法的参数c和g为例,使用狼群算法进行优化(Taking the parameters c and g of the optimized SVM algorithm as an example, we optimize it with a wolf group algorithm)
    2018-03-06 21:18:29下载
    积分:1
  • 696516资源总数
  • 106914会员总数
  • 0今日下载