登录
首页 » matlab » 雷达matlab仿真,波束形成,角度测量,跟踪等等

雷达matlab仿真,波束形成,角度测量,跟踪等等

于 2021-02-19 发布
0 268
下载积分: 1 下载次数: 25

代码说明:

说明:  波形设计算法,阵列信号处理等相关知识的介绍仿真等(Introduction and Simulation of waveform design algorithm, array signal processing and other related knowledge)

文件列表:

23\angle_delta.m, 2196 , 2014-05-15
23\angle_k.m, 3591 , 2014-05-19
23\angle_k2.m, 1322 , 2014-04-21
23\data_Position_RMSE_5261942.xls, 16896 , 2014-05-26
23\data_Position_RMSE_5261945.xls, 16896 , 2014-05-26
23\data_Position_RMSE_5261946.xls, 16896 , 2014-05-26
23\data_Position_RMSE_5261953.xls, 108544 , 2014-05-26
23\data_Position_RMSE_526202.xls, 79872 , 1990-05-29
23\data_Position_RMSE_5291628.xls, 57856 , 2014-05-29
23\data_Position_RMSE_529165.xls, 57856 , 2014-05-29
23\data_Position_RMSE_731017.xls, 62976 , 2014-07-03
23\data_Position_RMSE_731714.xls, 62976 , 2014-07-04
23\data_Position_RMSE_741136.xls, 62976 , 2014-07-06
23\data_Position_RMSE_74842.xls, 62976 , 2014-07-04
23\data_SNR_RMSE.xls, 17920 , 2014-05-16
23\data_SNR_RMSE_0519.xls, 17920 , 2014-05-19
23\data_SNR_RMSE_0520.xls, 17920 , 2014-05-20
23\data_SNR_RMSE_0520_a.xls, 17920 , 2014-05-21
23\data_SNR_RMSE_0520_b.xls, 17920 , 2014-05-22
23\data_SNR_RMSE_52216.xls, 17920 , 2014-05-22
23\data_SNR_RMSE_52616.xls, 17920 , 2014-05-26
23\data_SNR_RMSE_5261643.xls, 17920 , 2014-05-26
23\data_SNR_RMSE_5261649.xls, 17920 , 2014-05-26
23\data_SNR_RMSE_5261652.xls, 17920 , 2014-05-26
23\data_SNR_RMSE_5261655.xls, 17920 , 2014-05-26
23\data_SNR_RMSE_5261659.xls, 17920 , 2014-05-26
23\data_SNR_RMSE_5261713.xls, 17920 , 2014-05-26
23\data_SNR_RMSE_5261716.xls, 17920 , 2014-05-26
23\data_SNR_RMSE_5261719.xls, 17920 , 2014-05-26
23\data_SNR_RMSE_526172.xls, 17920 , 2014-05-26
23\data_SNR_RMSE_5261723.xls, 17920 , 2014-05-26
23\data_SNR_RMSE_5261726.xls, 17920 , 2014-05-26
23\data_SNR_RMSE_5261729.xls, 17920 , 2014-05-26
23\data_SNR_RMSE_5261733.xls, 17920 , 2014-05-26
23\data_SNR_RMSE_5261736.xls, 17920 , 2014-05-26
23\data_SNR_RMSE_5261739.xls, 17920 , 2014-05-26
23\data_SNR_RMSE_5261743.xls, 17920 , 2014-05-26
23\data_SNR_RMSE_5261746.xls, 17920 , 2014-05-26
23\data_SNR_RMSE_5261749.xls, 17920 , 2014-05-26
23\data_SNR_RMSE_5261753.xls, 17920 , 2014-05-26
23\data_SNR_RMSE_5261756.xls, 17920 , 2014-05-26
23\data_SNR_RMSE_5261759.xls, 17920 , 2014-05-26
23\data_SNR_RMSE_526176.xls, 17920 , 2014-05-26
23\data_SNR_RMSE_526179.xls, 17920 , 2014-05-26
23\data_SNR_RMSE_5261813.xls, 17920 , 2014-05-26
23\data_SNR_RMSE_5261816.xls, 17920 , 2014-05-26
23\data_SNR_RMSE_5261819.xls, 17920 , 2014-05-26
23\data_SNR_RMSE_5261823.xls, 17920 , 2014-05-26
23\data_SNR_RMSE_526183.xls, 17920 , 2014-05-26
23\data_SNR_RMSE_526186.xls, 17920 , 2014-05-26
23\data_SNR_RMSE_526189.xls, 17920 , 2014-05-26
23\data_SNR_RMSE_5291713.xls, 17920 , 2014-05-29
23\data_SNR_RMSE_5291717.xls, 17920 , 2014-05-29
23\data_SNR_RMSE_5291725.xls, 17920 , 2014-05-29
23\dbf_test_1.mat, 451 , 2014-06-16
23\dbf_test_2.mat, 453 , 2014-06-16
23\dbf_test_3.mat, 452 , 2014-06-16
23\Echo_MIMO_PCM.m, 3714 , 2014-04-30
23\echo_pa_hf.m, 7554 , 2014-04-28
23\echo_pcm_static.m, 1786 , 2014-04-21
23\error_alphar2013.m, 5125 , 2014-06-16
23\error_alphat2013.m, 3312 , 2013-06-07
23\error_angle.m, 367 , 2013-06-02
23\error_d.m, 3963 , 2014-06-16
23\error_d2013.m, 6414 , 2014-04-09
23\error_v2013.m, 4177 , 2013-06-08
23\gen_base.m, 2497 , 2014-04-18
23\Gen_st_vector0506.m, 1725 , 2014-04-28
23\Gen_st_vector0524.m, 2123 , 2014-04-28
23\Gen_st_vector_cs.m, 2139 , 2014-05-14
23\hs_err_pid5552.log, 23348 , 1990-05-29
23\main_23.m, 57186 , 2014-06-16
23\main_23_0616.m, 60040 , 2014-07-04
23\matching10.m, 1198 , 2013-06-02
23\matching10_2013.m, 469 , 2014-05-13
23\monoPA.m, 1243 , 2014-05-30
23\monopulse_vec.m, 868 , 2014-05-15
23\multi_par.m, 3395 , 2014-05-30
23\mydata.xls, 17408 , 2014-04-30
23\papc-16-128.mat, 275 , 2013-06-02
23\papc-16-256.mat, 352 , 2013-04-18
23\rdbf.m, 1219 , 2014-06-16
23\rExtract1.m, 594 , 2014-06-16
23\rExtract2.m, 294 , 2013-06-02
23\rExtract20130526.m, 595 , 2013-06-07
23\sigma_thetar.m, 0 , 2014-05-20
23\SNR_RMSE0507.fig, 2702 , 2014-05-07
23\sypc-16-1024.mat, 3583 , 2013-06-02
23\sypc-16-2048.mat, 6959 , 2013-06-02
23\sypc-16-256.mat, 1060 , 2013-06-02
23\Target_Echo_PCM.m, 5266 , 2014-04-21
23\testdata2.xls, 16896 , 2014-04-30
23\transmit_2013.m, 2401 , 2014-05-14
23\t_mtd.m, 707 , 2014-06-16
23, 0 , 2014-07-06

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

  • Archive
    PCA 数据降维 PTYTHON 数据分析/挖掘(PCA dimensionality reduction data mining/analysis)
    2020-06-21 15:40:02下载
    积分:1
  • python-knn
    主要利用Python软件,利用KNN算法对垃圾邮件进行分类(This paper mainly uses Python software to classify spam mail by using KNN algorithm)
    2017-11-10 15:46:56下载
    积分:1
  • my_apriori
    很好用的关联规则挖掘经典算法,推荐使用。包括支持度、置信度、提升度,输出结果到excel文件(Good use of association rules mining classic algorithm, recommended)
    2018-11-14 15:51:16下载
    积分:1
  • boston_housing
    说明:  采用机器学习预测房价.使用波士顿房屋信息数据来训练和测试一个模型,并对模型的性能和预测能力进行评估。(Using Machine Learning to Predict House Prices)
    2019-10-04 11:48:44下载
    积分:1
  • 聚类指标小结
    说明:  聚类评价指标的各种说明,非常详细,请仔细阅读。(Cluster evaluation indicators of various descriptions, very detailed.)
    2020-06-19 05:20:01下载
    积分:1
  • 77257795PCA_yuandaima
    PCA源程序,主元分析源程序,可以用于变量的特征提取(PCA source code, principal component analysis source, can be used for variable feature extraction)
    2017-06-04 21:05:56下载
    积分:1
  • k-means-for-iris
    说明:  利用K均值聚类对鸢尾花样本进行聚类的matlab程序,包含源代码、样本数据、聚类结果(The matlab program of clustering iris samples by K-means clustering, including source code, sample data and clustering results)
    2020-10-17 20:27:27下载
    积分:1
  • Kares入门资料打包
    深度学习框架Keras入门资料,里面的代码包括课件和DEMO有利于新书入门学习,简单易懂(Keras Introductory Information of Deep Learning Framework, which includes courseware and DEMO, is helpful for introductory learning of new books. It is easy to understand.)
    2020-06-17 17:00:01下载
    积分:1
  • Ecalt算法
    Eclat算法是一种深度优先算法,采用垂直数据表示形式,在概念格理论的基础上利用基于前缀的等价关系将搜索空间(概念格)划分为较小的子空间(子概念格)。Eclat算法采用方法二计算支持度。对候选k项集进行支持度计算时,不需再次扫描数据库,仅在一次扫描数据库后得到每个1项集的支持度,而候选k项集的支持度就是在对k-1项集进行交集操作后得到的该k项集Tidset中元素的个数。本算法利用diffset数据格式实现。
    2022-03-02 17:06:13下载
    积分:1
  • Tensor-Factorization-HOSVD-iterative-master
    hosvd 迭代分解,很好用,是一个硕士论文里的代码(terative HOSVD algorithm to decompose tensor and find its Singular factors in each mode.)
    2021-03-27 11:39:12下载
    积分:1
  • 696518资源总数
  • 104432会员总数
  • 16今日下载