登录
首页 » matlab » GMM_UBM

GMM_UBM

于 2014-10-19 发布 文件大小:3KB
0 210
下载积分: 1 下载次数: 55

代码说明:

  Combine GMM and UBM in speaker recognition

文件列表:

HuanluyenGMM.m,455,2012-12-13
HuanluyenUBM.m,4622,2014-02-23

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

  • dq_to_abc
    for simulink clarke transform
    2010-07-14 17:06:26下载
    积分:1
  • cubo
    this file contains some m-files about calculating the fractional fourier transform
    2010-10-24 18:16:25下载
    积分:1
  • BPSK_BER_GAIN_OFDM
    BPSK_BER_GAIN_OFDM Phase Shift Keying
    2015-04-02 01:07:32下载
    积分:1
  • A-Guide-to-MATLAB-for-Beginners
    说明:  一本matlab初学者的入门级经典书籍编程人员案头必备的一本参考书籍,英文版,有助于提高英文及编程技术.(An entry-level matlab beginner programmers classic books necessary for a desk reference book, in English, help to improve English and programming.)
    2011-02-19 11:18:14下载
    积分:1
  • Lossy_compression_DCT
    it is matlab code for compress the image
    2014-12-10 12:45:03下载
    积分:1
  • FastFloyd
    floyd warshall algorithm
    2010-12-05 23:54:15下载
    积分:1
  • PDCCH
    PDCCH的链路仿真,需要的朋友可以参考一下。(PDCCH link simulation, the needs of friends can reference.)
    2009-12-28 20:35:09下载
    积分:1
  • mfiles
    matlab6.5的源代码,包含了所有实例的源代码,请多多支持!!(matlab6.5 source code, contains all instances of the source code, a lot of support! !)
    2011-06-21 20:57:49下载
    积分:1
  • Collocation
    this code for least square collocation estimation
    2010-10-26 11:28:56下载
    积分:1
  • shenjingwangluo
    T=[1 0 0 1 0 0 1 0 0 0 1 0 0 1 0 0 1 0 0 0 1 0 0 1 0 0 1] 输入向量的最大值和最小值 threshold=[0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1] net=newff(threshold,[31 3],{ tansig , logsig }, trainlm ) 训练次数为1000,训练目标为0.01,学习速率为0.1 net.trainParam.epochs=1000 net.trainParam.goal=0.01 LP.lr=0.1 net = train(net,P,T) 测试数据,和训练数据不一致 P_test=[0.2101 0.0950 0.1298 0.1359 0.2601 0.1001 0.0753 0.0890 0.0389 0.1451 0.0128 0.1590 0.2452 0.0512 0.1319 0.2593 0.1800 0.0711 0.2801 0.1501 0.1298 0.1001 0.1891 0.2531 0.0875 0.0058 0.1803 0.0992 0.0802 0.1002 (T = [1 0 0 1 0 0 1 0 0 0 1 0 0 1 0 0 1 0 0 0 1 0 0 1 0 0 1] ' of the maximum and minimum input vector threshold = [0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1] net = newff (threshold, [31 3], {' tansig' , ' logsig' }, ' trainlm' ) training times for the 1000 target of 0.01 training, learning rate of 0.1 net.trainParam.epochs = 1000 net. trainParam.goal = 0.01 LP.lr = 0.1 net = train (net, P, T) test data, and training data inconsistencies P_test = [0.2101 0.0950 0.1298 0.1359 0.2601 0.1001 0.0753 0.0890 0.0389 0.1451 0.0128 0.1590 0.2452 0.0512 0.1319 0.2593 0.1800 0.0711 0.2801 0.1501 0.1298 0.1001 0.1891 0.2531 0.0875 0.0058 0.1803 0.0992 0.0802 0.1002 )
    2011-05-21 16:47:44下载
    积分:1
  • 696516资源总数
  • 106914会员总数
  • 0今日下载