登录
首页 » matlab » hmm_matlab

hmm_matlab

于 2020-09-02 发布 文件大小:3934KB
0 251
下载积分: 1 下载次数: 88
我要下载

代码说明：

  基于隐马尔科夫模型HMM的人脸识别程序，使用Matlab编写，提取的人脸识别特征为DCT系数(it is face detection codes based on HMM Model ，you can run iton Matlab，the feature from face is DCT)

文件列表：

hmm_matlab
..........\dct_hmm.m,4871,2013-04-10
..........\dct_test1.m,2320,2013-04-10
..........\em_converged.m,1189,2005-04-25
..........\fwdback.m,7194,2010-08-30
..........\isposdef.m,289,2005-04-25
..........\KPMstats
..........\........\#histCmpChi2.m#,267,2005-05-03
..........\........\beta_sample.m,1955,2005-04-25
..........\........\chisquared_histo.m,199,2005-04-25
..........\........\chisquared_prob.m,1326,2005-04-25
..........\........\chisquared_readme.txt,1389,2005-04-25
..........\........\chisquared_table.m,2127,2005-04-25
..........\........\clg_Mstep.m,5884,2005-04-25
..........\........\clg_Mstep_simple.m,1463,2005-04-25
..........\........\clg_prob.m,421,2005-04-25
..........\........\condGaussToJoint.m,646,2005-04-25
..........\........\condgaussTrainObserved.m,908,2005-04-25
..........\........\condgauss_sample.m,351,2005-04-25
..........\........\cond_indep_fisher_z.m,3789,2005-04-25
..........\........\convertBinaryLabels.m,101,2005-04-25
..........\........\cwr_demo.m,3513,2005-04-25
..........\........\cwr_em.m,4912,2005-04-25
..........\........\cwr_predict.m,1677,2005-04-25
..........\........\cwr_prob.m,1011,2005-04-25
..........\........\cwr_readme.txt,534,2005-04-25
..........\........\cwr_test.m,2436,2005-04-25
..........\........\dirichletpdf.m,1049,2005-05-22
..........\........\dirichletrnd.m,1049,2005-05-22
..........\........\dirichlet_sample.m,582,2005-04-25
..........\........\distchck.m,3836,2005-04-25
..........\........\eigdec.m,1535,2005-04-25
..........\........\est_transmat.m,535,2005-04-25
..........\........\fit_paritioned_model_testfn.m,103,2005-04-25
..........\........\fit_partitioned_model.m,2290,2005-04-25
..........\........\fwdback.m,7194,2010-08-30
..........\........\gamma_sample.m,3144,2005-04-25
..........\........\gaussian_prob.asv,852,2009-08-05
..........\........\gaussian_prob.m,853,2009-08-05
..........\........\gaussian_sample.m,659,2005-04-25
..........\........\histCmpChi2.m,394,2005-05-03
..........\........\histCmpChi2.m~,353,2005-05-03
..........\........\KLgauss.m,342,2005-04-25
..........\........\linear_regression.m,2038,2005-04-25
..........\........\logist2.m,3050,2005-04-25
..........\........\logist2Apply.m,365,2005-04-25
..........\........\logist2ApplyRegularized.m,91,2005-04-25
..........\........\logist2Fit.m,593,2005-04-25
..........\........\logist2FitRegularized.m,411,2005-04-25
..........\........\logistK.m,7540,2005-04-25
..........\........\logistK_eval.m,2372,2005-04-25
..........\........\marginalize_gaussian.m,293,2005-04-25
..........\........\matrix_normal_pdf.m,346,2005-04-25
..........\........\matrix_T_pdf.m,430,2005-04-25
..........\........\mc_stat_distrib.m,790,2005-04-25
..........\........\mhmm_em.m,5745,2010-08-30
..........\........\mhmm_logprob.m,960,2010-08-30
..........\........\mixgauss_classifier_apply.m,534,2005-04-25
..........\........\mixgauss_classifier_train.m,1377,2005-04-25
..........\........\mixgauss_em.m,2252,2005-04-25
..........\........\mixgauss_init.m,1357,2005-04-25
..........\........\mixgauss_Mstep.m,3448,2009-08-16
..........\........\mixgauss_prob.asv,4349,2009-08-16
..........\........\mixgauss_prob.m,4375,2009-08-16
..........\........\mixgauss_prob_test.m,2320,2005-04-25
..........\........\mixgauss_sample.m,734,2005-04-25
..........\........\mkPolyFvec.m,576,2005-04-25
..........\........\mk_unit_norm.m,280,2005-04-25
..........\........\multinomial_prob.m,567,2005-04-25
..........\........\multinomial_sample.m,577,2005-04-25
..........\........\multipdf.m,1192,2005-05-22
..........\........\multirnd.m,1161,2005-05-22
..........\........\normal_coef.m,205,2005-04-25
..........\........\partial_corr_coef.m,844,2005-04-25
..........\........\parzen.m,2478,2005-04-25
..........\........\parzenC.c,2790,2005-04-25
..........\........\parzenC.dll,49152,2005-04-25
..........\........\parzenC.mexglx,20215,2005-04-25
..........\........\parzenC_test.m,250,2005-04-25
..........\........\parzen_fit_select_unif.m,1668,2005-04-25
..........\........\pca.m,1077,2005-04-25
..........\........\README.txt,156,2005-04-25
..........\........\rndcheck.m,8072,2005-04-25
..........\........\sample.m,358,2005-04-25
..........\........\sample_discrete.m,1002,2005-04-25
..........\........\sample_gaussian.m,524,2005-04-25
..........\........\standardize.m,462,2005-05-03
..........\........\standardize.m~,446,2005-04-25
..........\........\student_t_logprob.m,521,2005-04-25
..........\........\student_t_prob.m,643,2005-04-25
..........\........\test_dir.m,368,2005-05-22
..........\........\unidrndKPM.m,122,2005-05-31
..........\........\unidrndKPM.m~,85,2005-05-31
..........\........\unif_discrete_sample.m,258,2005-04-25
..........\........\viterbi_path.m,1541,2010-08-30
..........\........\weightedRegression.m,1343,2005-04-25
..........\KPMtools
..........\........\approxeq.m,489,2005-04-25
..........\........\approx_unique.m,852,2005-04-25
..........\........\argmax.m,347,2005-04-25

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

  • cooccurrence
    code for coocurrence matrix
    2009-10-24 23:36:11下载
    积分：1
  • New-Folder
    dwt based watermarking and enhanced results .............
    2012-02-06 14:43:04下载
    积分：1
  • Decoder
    一种应用于咬尾卷积码的译码算法，基于维特比译码算法(A decoding method applied to tail biting convolutional codes of the matlab program)
    2021-05-13 17:30:02下载
    积分：1
  • MATLAB
    利用SVM对进行模糊信息粒化后的玉米每日期货价格进行变化趋势和变化空间的进行预测。选取的数据为2006年1月4日到2015年12月18日这一期间内C05玉米期货每交易日的开盘价，预测的内容为下五个交易日内玉米期货价格的变化趋势与变化空间，即预测21日、22日、23日、24日、25日这五个交易日内玉米期货价格的变化趋势（整体变大或者变小）和变化的范围空间。需要搭建libsvm环境( U5229 u5BF9 u8FDB u8FDB u884C u8A1 u7CCA u0F1 u606F u7C92 u5316 u540E u7684 u7389 u7C73 u6BCF u65E5 u671F u8D27 u4EF7 u683C u8FDB u884C u53D8 u5316 U8D8B u52BF u53D u53A u53A u7164 u7644 u7R4 U65E5 u8FD9 u4E00 u671F u952F0 u5186 u5186 u7R4 u7R3 u7R3 U4E0B u4E9 u4E2A u4E4 u4134 u653 u5188 u5D3 U988 u6D3 u6E2 u0E1 u4E2 u4E2 u4E2 u4E3 u64E5 u65E5 u65E5 u65E5 u65E5 U53D8 u5316 u52B0 u52BF uFF08 u6574 u4D53 u53D8 u5927 u6216 u8005 u53D8 u5C0F uFF09 u548C u53D8 u5316 u7684 u8303 u56F4 u7A7A u95F4 u3002 u9700 u8981 U642D u5EFAlibsvm u73AF u5883)
    2017-05-09 20:07:54下载
    积分：1
  • SIT
    利用matlab编程实现含负折射材料的表面波和波导特性，有界面！(Matlab Programming with the use of negative refraction of surface waves and waveguide material properties, have interface!)
    2007-09-24 15:45:58下载
    积分：1
  • 大跨结构、高耸结构随机风荷载数值模拟
    大跨结构、高耸结构随机风荷载数值模拟，方便快捷、使用。(Span structures, the towering structure stochastic numerical simulation of wind loads, convenient to use.)
    2010-12-03 15:13:27下载
    积分：1
  • nn1
    最近邻算法结合卡尔曼滤波算法实现多目标跟踪(Nearest-neighbor algorithm for multi-target tracking)
    2021-04-21 18:58:49下载
    积分：1
  • kaiguandianyuan
    这是具有功率因数校正的开关电源的MATLAB/SIMULINK仿真模型，希望对有用的人，有所帮助！(this is a simulink model of power supply with PFC, which is useful for those who study on this!)
    2009-07-10 15:11:41下载
    积分：1
  • XieLvDuiShu2
    1、利用自相关法找出含有大量数据的周期信号的周期 2、利用互相关对齐含有大量数据的多路采样信号以便分析 3、使用分段平滑经过求导后的含有干扰的图像曲线(1, using the autocorrelation method contains large amounts of data to identify the period of the periodic signal 2, using the cross-correlation contains a large amount of data aligned with the sampling signal for the multiplexed analysis, the use of segmented through derivative after smoothing with interference by the image curve)
    2013-10-22 16:37:12下载
    积分：1
  • mimo-ofdm
    主要是将MIMO-OFDM系统中的空时分组码与MIMO系统中的空时分组码进行对比，着重突出MIMO-OFDM的优点。(Mainly in the MIMO-OFDM systems with space-time block codes in MIMO systems space-time block codes are compared to highlight the advantages of MIMO-OFDM. )
    2011-12-18 17:55:53下载
    积分：1
  • 696516资源总数
  • 106914会员总数
  • 0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© 2019-2026 | 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！