登录
首页 » matlab » FastSVDD-master

FastSVDD-master

于 2021-03-08 发布
0 179
下载积分: 1 下载次数: 4
我要下载

代码说明：

说明：  支持向量数据描述（Support Vector Data Description，SVDD）是一种单值分类算法，能够实现目标样本和非目标样本的区分，通常应用于异常检测和故障检测等领域。(Support vector data description (SVDD) is a single valued classification algorithm, which can distinguish target samples from non target samples. It is usually used in anomaly detection and fault detection.)

文件列表：

FastSVDD-master, 0 , 2015-05-19
FastSVDD-master\.gitignore, 27 , 2015-05-19
FastSVDD-master\Code, 0 , 2015-05-19
FastSVDD-master\Code\Ellipse, 0 , 2015-05-19
FastSVDD-master\Code\Ellipse\fsvdd, 0 , 2015-05-19
FastSVDD-master\Code\Ellipse\fsvdd\computeKgm.m, 812 , 2015-05-19
FastSVDD-master\Code\Ellipse\fsvdd\decn.png, 10354 , 2015-05-19
FastSVDD-master\Code\Ellipse\fsvdd\ellipse.mat, 6342 , 2015-05-19
FastSVDD-master\Code\Ellipse\fsvdd\fsvdd_predict.m, 939 , 2015-05-19
FastSVDD-master\Code\Ellipse\fsvdd\fsvdd_train.m, 2849 , 2015-05-19
FastSVDD-master\Code\Ellipse\fsvdd\load_data.m, 499 , 2015-05-19
FastSVDD-master\Code\Ellipse\fsvdd\svkernel_new.m, 2573 , 2015-05-19
FastSVDD-master\Code\Ellipse\fsvdd\svtol.m, 406 , 2015-05-19
FastSVDD-master\Code\Ellipse\fsvdd\test_fsvdd.m, 2788 , 2015-05-19
FastSVDD-master\Code\Ellipse\gen_data.m, 732 , 2015-05-19
FastSVDD-master\Code\Ellipse\svdd, 0 , 2015-05-19
FastSVDD-master\Code\Ellipse\svdd\computeKgm.m, 812 , 2015-05-19
FastSVDD-master\Code\Ellipse\svdd\data.png, 8745 , 2015-05-19
FastSVDD-master\Code\Ellipse\svdd\decn.png, 10336 , 2015-05-19
FastSVDD-master\Code\Ellipse\svdd\ellipse.mat, 6342 , 2015-05-19
FastSVDD-master\Code\Ellipse\svdd\load_data.m, 531 , 2015-05-19
FastSVDD-master\Code\Ellipse\svdd\svdd_predict.m, 1042 , 2015-05-19
FastSVDD-master\Code\Ellipse\svdd\svdd_train.m, 2670 , 2015-05-19
FastSVDD-master\Code\Ellipse\svdd\svkernel_new.m, 2586 , 2015-05-19
FastSVDD-master\Code\Ellipse\svdd\svtol.m, 406 , 2015-05-19
FastSVDD-master\Code\Ellipse\svdd\test_svdd.m, 2609 , 2015-05-19
FastSVDD-master\Code\FisherIris, 0 , 2015-05-19
FastSVDD-master\Code\FisherIris\fsvdd, 0 , 2015-05-19
FastSVDD-master\Code\FisherIris\fsvdd\Results.txt, 1520 , 2015-05-19
FastSVDD-master\Code\FisherIris\fsvdd\computeKgm.m, 596 , 2015-05-19
FastSVDD-master\Code\FisherIris\fsvdd\computeResults.m, 1616 , 2015-05-19
FastSVDD-master\Code\FisherIris\fsvdd\computeResults_fpt.m, 1622 , 2015-05-19
FastSVDD-master\Code\FisherIris\fsvdd\data.mat, 8326 , 2015-05-19
FastSVDD-master\Code\FisherIris\fsvdd\fsvdd_predict.m, 939 , 2015-05-19
FastSVDD-master\Code\FisherIris\fsvdd\fsvdd_train.m, 2849 , 2015-05-19
FastSVDD-master\Code\FisherIris\fsvdd\fsvdd_train_fpt.m, 3419 , 2015-05-19
FastSVDD-master\Code\FisherIris\fsvdd\load_data.m, 3962 , 2015-05-19
FastSVDD-master\Code\FisherIris\fsvdd\svkernel_new.m, 2585 , 2015-05-19
FastSVDD-master\Code\FisherIris\fsvdd\svtol.m, 406 , 2015-05-19
FastSVDD-master\Code\FisherIris\fsvdd\test_fsvdd.m, 1721 , 2015-05-19
FastSVDD-master\Code\FisherIris\fsvdd\test_fsvdd_fpt.m, 1798 , 2015-05-19
FastSVDD-master\Code\FisherIris\mlffnn, 0 , 2015-05-19
FastSVDD-master\Code\FisherIris\mlffnn\load_data.m, 4111 , 2015-05-19
FastSVDD-master\Code\FisherIris\mlffnn\mlffnn.m, 4102 , 2015-05-19
FastSVDD-master\Code\FisherIris\svdd, 0 , 2015-05-19
FastSVDD-master\Code\FisherIris\svdd\Results.txt, 920 , 2015-05-19
FastSVDD-master\Code\FisherIris\svdd\computeKgm.m, 612 , 2015-05-19
FastSVDD-master\Code\FisherIris\svdd\computeResults.m, 1552 , 2015-05-19
FastSVDD-master\Code\FisherIris\svdd\data.mat, 8326 , 2015-05-19
FastSVDD-master\Code\FisherIris\svdd\iris_1.png, 5625 , 2015-05-19
FastSVDD-master\Code\FisherIris\svdd\iris_2.png, 5258 , 2015-05-19
FastSVDD-master\Code\FisherIris\svdd\load_data.m, 3943 , 2015-05-19
FastSVDD-master\Code\FisherIris\svdd\svdd_predict.m, 1042 , 2015-05-19
FastSVDD-master\Code\FisherIris\svdd\svdd_train.m, 3003 , 2015-05-19
FastSVDD-master\Code\FisherIris\svdd\svkernel_new.m, 2586 , 2015-05-19
FastSVDD-master\Code\FisherIris\svdd\svtol.m, 406 , 2015-05-19
FastSVDD-master\Code\FisherIris\svdd\test_svdd.m, 1622 , 2015-05-19
FastSVDD-master\Code\README.txt, 1087 , 2015-05-19
FastSVDD-master\Code\Wine, 0 , 2015-05-19
FastSVDD-master\Code\Wine\fsvdd, 0 , 2015-05-19
FastSVDD-master\Code\Wine\fsvdd\Results.txt, 898 , 2015-05-19
FastSVDD-master\Code\Wine\fsvdd\computeKgm.m, 596 , 2015-05-19
FastSVDD-master\Code\Wine\fsvdd\computeResults.m, 1556 , 2015-05-19
FastSVDD-master\Code\Wine\fsvdd\computeResults_fpt.m, 1583 , 2015-05-19
FastSVDD-master\Code\Wine\fsvdd\fsvdd_predict.m, 939 , 2015-05-19
FastSVDD-master\Code\Wine\fsvdd\fsvdd_train.m, 2855 , 2015-05-19
FastSVDD-master\Code\Wine\fsvdd\fsvdd_train_fpt.m, 3786 , 2015-05-19
FastSVDD-master\Code\Wine\fsvdd\load_data.m, 3271 , 2015-05-19
FastSVDD-master\Code\Wine\fsvdd\svkernel_new.m, 2587 , 2015-05-19
FastSVDD-master\Code\Wine\fsvdd\svtol.m, 406 , 2015-05-19
FastSVDD-master\Code\Wine\fsvdd\test_fsvdd.m, 1880 , 2015-05-19
FastSVDD-master\Code\Wine\fsvdd\test_fsvdd_fpt.m, 1943 , 2015-05-19
FastSVDD-master\Code\Wine\mlffnn, 0 , 2015-05-19
FastSVDD-master\Code\Wine\mlffnn\load_data.m, 3488 , 2015-05-19
FastSVDD-master\Code\Wine\mlffnn\mlffnn.m, 4289 , 2015-05-19
FastSVDD-master\Code\Wine\svdd, 0 , 2015-05-19
FastSVDD-master\Code\Wine\svdd\Results.txt, 621 , 2015-05-19
FastSVDD-master\Code\Wine\svdd\computeKgm.m, 596 , 2015-05-19
FastSVDD-master\Code\Wine\svdd\computeResults.m, 1536 , 2015-05-19
FastSVDD-master\Code\Wine\svdd\data.mat, 29144 , 2015-05-19
FastSVDD-master\Code\Wine\svdd\load_data.m, 3272 , 2015-05-19
FastSVDD-master\Code\Wine\svdd\svdd_predict.m, 1042 , 2015-05-19
FastSVDD-master\Code\Wine\svdd\svdd_train.m, 2718 , 2015-05-19
FastSVDD-master\Code\Wine\svdd\svkernel_new.m, 2585 , 2015-05-19
FastSVDD-master\Code\Wine\svdd\svtol.m, 406 , 2015-05-19
FastSVDD-master\Code\Wine\svdd\test_svdd.m, 1929 , 2015-05-19
FastSVDD-master\Code\overlapping, 0 , 2015-05-19
FastSVDD-master\Code\overlapping\fsvdd, 0 , 2015-05-19
FastSVDD-master\Code\overlapping\fsvdd\Results.txt, 2680 , 2015-05-19
FastSVDD-master\Code\overlapping\fsvdd\computeKgm.m, 612 , 2015-05-19
FastSVDD-master\Code\overlapping\fsvdd\decn_1.png, 16694 , 2015-05-19
FastSVDD-master\Code\overlapping\fsvdd\decn_1_fpt.png, 16633 , 2015-05-19
FastSVDD-master\Code\overlapping\fsvdd\decn_2.png, 16192 , 2015-05-19
FastSVDD-master\Code\overlapping\fsvdd\decn_2_fpt.png, 16237 , 2015-05-19
FastSVDD-master\Code\overlapping\fsvdd\decn_3.png, 15679 , 2015-05-19
FastSVDD-master\Code\overlapping\fsvdd\decn_3_fpt.png, 15699 , 2015-05-19
FastSVDD-master\Code\overlapping\fsvdd\decn_4.png, 15479 , 2015-05-19
FastSVDD-master\Code\overlapping\fsvdd\decn_4_fpt.png, 15444 , 2015-05-19
FastSVDD-master\Code\overlapping\fsvdd\fsvdd_predict.m, 1007 , 2015-05-19
FastSVDD-master\Code\overlapping\fsvdd\fsvdd_train.m, 2931 , 2015-05-19

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

  • getPDF1
    In this paper, we investigate the timing and carrier frequency offset (CFO) synchronization problem in decode and forward cooperative systems operating over frequency selective channels. A training sequence which consists of one orthogonal frequency-division multiplexing (OFDM) block having a tile structure in the frequency domain is proposed to perform synchronization. Timing offsets are estimated using correlation-type algorithms. By inserting some null subcarriers in the proposed tile structure, we propose a computationally efficient subspace decomposition- based algorithm for CFO estimation. The issue of optimal tile length is studied both theoretically and through simulations. By judiciously designing the tile size of the pilot, the proposed algorithms are shown to have better performance, in terms of synchronization errors and bit error rate, than the time-division multiplexing-based training method and the computationally demanding space-alternating generalized expectation-maximization
    2010-08-11 18:19:11下载
    积分：1
  • Demo_Greedy
    In this program we demonstrate the MP, OMP, WMP, and Thresh algorithm, by running them on a set of test signals and checking wether they provide the desired outcome
    2013-10-02 20:23:36下载
    积分：1
  • ORGANISER-LE
    program simulink about mimo system
    2012-02-07 19:54:04下载
    积分：1
  • G
    说明：  如何获取MATLAB句柄的说明 Getting a handle on MATLAB graphics 英文版！(How to obtain a description of MATLAB Handle Getting a handle on MATLAB graphics in English!)
    2007-12-20 04:51:38下载
    积分：1
  • Ch02
    matlab 可视化 微分方程 物理 算法 超越方程 科学计算 数学变换 最值问题 图像增强 图形界面 线性方程 元胞自动机 晶体生长 金融(physical algorithm matlab visualization in scientific computing differential equations of mathematical transformations beyond the most value problem of linear equations graphical image enhancement of cellular automata Crystal Growth Finance)
    2014-02-02 11:08:28下载
    积分：1
  • fallingball
    描述小球在水平和竖直弹簧上的跳动模型（原创）(Describe the ball in the horizontal and vertical jumps on the spring model (original))
    2010-07-09 00:29:28下载
    积分：1
  • sc
    说明：  SC is a useful function for displaying rich image data, of use to anyone wishing to visualize and save 2D data in ways beyond that which MATLAB built-in functions allow. This function can be used in place of IMAGE, IMAGESC and IMSHOW, but does so much more. It is fast and displays images as they should be - correct aspect ratio, integer magnification, no axes. In addition, it can return the image as an output variable - useful for saving to disk, texture mapping surfaces, and post-rendering manipulation such as overlaying/combining two or more images.(SC is a useful function for displaying rich image data, of use to anyone wishing to visualize and save 2D data in ways beyond that which MATLAB built-in functions allow. This function can be used in place of IMAGE, IMAGESC and IMSHOW, but does so much more. It is fast and displays images as they should be- correct aspect ratio, integer magnification, no axes. In addition, it can return the image as an output variable- useful for saving to disk, texture mapping surfaces, and post-rendering manipulation such as overlaying/combining two or more images.)
    2009-08-25 19:00:06下载
    积分：1
  • dmc
    DMC控制 当系统的参数知道很少时可以利用这种方法进行运算 从而很好的控制(DMC control parameters when the system knows very little use of this method can well control operations to)
    2011-09-19 16:54:14下载
    积分：1
  • HMM
    matlab的HMM训练程序，可用于语音信号的训练与处理。(matlab HMM training program, can be used for the training of the voice signal processing.)
    2013-04-02 11:09:25下载
    积分：1
  • dpdsimulation
    DPD预失真算法的matlab仿真实现,其中包括了LMS,RLS,LS等自适应算法(the digital predistortion algorithm basic on matlab)
    2021-03-18 14:59:20下载
    积分：1
  • 696518资源总数
  • 106227会员总数
  • 11今日下载

热门标签

Visual C++ matlab C/C++ Java Others Unix_Linux EasyLanguage易语言 Visual Basic C# PDF C++ Delphi VHDL ASP WINDOWS
热门下载

Copyright© 2019-2025 | Powered by Imdn | 浙ICP备16007336号 | IMDN交流 | 联系客服（QQ：3324461878）

本网站资源收集自网络及网站用户上传，若有侵权请邮件至（3324461878@qq.com），核实后我们会在24小时内删除，谢谢！