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libsvm-3.18

于 2018-12-18 发布 文件大小:680KB
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下载积分: 1 下载次数: 2

代码说明:

  工具箱,做svm算法时使用的,将其放在toolbox文件夹下,开始matlab运行时调整好路径即可使用(libsvm Toolbox.Used when doing the svm algorithm, put it in the toolbox folder, start the matlab runtime to adjust the path to use)

文件列表:

libsvm-3.18, 0 , 2014-07-22
libsvm-3.18\COPYRIGHT, 1497 , 2014-04-01
libsvm-3.18\FAQ.html, 78971 , 2014-04-01
libsvm-3.18\heart_scale, 27670 , 2014-04-01
libsvm-3.18\java, 0 , 2014-07-22
libsvm-3.18\java\libsvm, 0 , 2014-07-22
libsvm-3.18\java\libsvm.jar, 51916 , 2014-04-01
libsvm-3.18\java\libsvm\svm.java, 63803 , 2014-04-01
libsvm-3.18\java\libsvm\svm.m4, 63095 , 2014-04-01
libsvm-3.18\java\libsvm\svm_model.java, 868 , 2014-04-01
libsvm-3.18\java\libsvm\svm_node.java, 115 , 2014-04-01
libsvm-3.18\java\libsvm\svm_parameter.java, 1288 , 2014-04-01
libsvm-3.18\java\libsvm\svm_print_interface.java, 87 , 2014-04-01
libsvm-3.18\java\libsvm\svm_problem.java, 136 , 2014-04-01
libsvm-3.18\java\Makefile, 624 , 2014-04-01
libsvm-3.18\java\svm_predict.java, 4950 , 2014-04-01
libsvm-3.18\java\svm_scale.java, 8944 , 2014-04-01
libsvm-3.18\java\svm_toy.java, 12269 , 2014-04-01
libsvm-3.18\java\svm_train.java, 8355 , 2014-04-01
libsvm-3.18\java\test_applet.html, 81 , 2014-04-01
libsvm-3.18\Makefile, 732 , 2014-04-01
libsvm-3.18\Makefile.win, 1084 , 2014-04-01
libsvm-3.18\matlab, 0 , 2014-07-22
libsvm-3.18\matlab\libsvmread.c, 4069 , 2014-04-01
libsvm-3.18\matlab\libsvmread.mexw64, 10752 , 2014-04-01
libsvm-3.18\matlab\libsvmwrite.c, 2359 , 2014-04-01
libsvm-3.18\matlab\libsvmwrite.mexw64, 9728 , 2014-04-01
libsvm-3.18\matlab\make.m, 798 , 2014-04-01
libsvm-3.18\matlab\Makefile, 1240 , 2014-04-01
libsvm-3.18\matlab\README, 9733 , 2014-04-01
libsvm-3.18\matlab\svmpredict.c, 9823 , 2014-04-01
libsvm-3.18\matlab\svmpredict.mexw64, 24064 , 2014-04-01
libsvm-3.18\matlab\svmtrain.c, 11606 , 2014-04-01
libsvm-3.18\matlab\svmtrain.mexw64, 61952 , 2014-04-01
libsvm-3.18\matlab\svm_model_matlab.c, 8241 , 2014-04-01
libsvm-3.18\matlab\svm_model_matlab.h, 201 , 2014-04-01
libsvm-3.18\python, 0 , 2014-07-22
libsvm-3.18\python\Makefile, 32 , 2014-04-01
libsvm-3.18\python\README, 11908 , 2014-04-01
libsvm-3.18\python\svm.py, 9469 , 2014-04-01
libsvm-3.18\python\svm.pyc, 13388 , 2014-04-02
libsvm-3.18\python\svmutil.py, 8537 , 2014-04-01
libsvm-3.18\README, 28436 , 2014-04-01
libsvm-3.18\svm-predict.c, 5536 , 2014-04-01
libsvm-3.18\svm-scale.c, 8504 , 2014-04-01
libsvm-3.18\svm-toy, 0 , 2014-07-22
libsvm-3.18\svm-toy\gtk, 0 , 2014-07-22
libsvm-3.18\svm-toy\gtk\callbacks.cpp, 10308 , 2014-04-01
libsvm-3.18\svm-toy\gtk\callbacks.h, 1765 , 2014-04-01
libsvm-3.18\svm-toy\gtk\interface.c, 6457 , 2014-04-01
libsvm-3.18\svm-toy\gtk\interface.h, 203 , 2014-04-01
libsvm-3.18\svm-toy\gtk\main.c, 398 , 2014-04-01
libsvm-3.18\svm-toy\gtk\Makefile, 573 , 2014-04-01
libsvm-3.18\svm-toy\gtk\svm-toy.glade, 6402 , 2014-04-01
libsvm-3.18\svm-toy\qt, 0 , 2014-07-22
libsvm-3.18\svm-toy\qt\Makefile, 392 , 2014-04-01
libsvm-3.18\svm-toy\qt\svm-toy.cpp, 9744 , 2014-04-01
libsvm-3.18\svm-toy\windows, 0 , 2014-07-22
libsvm-3.18\svm-toy\windows\svm-toy.cpp, 11503 , 2014-04-01
libsvm-3.18\svm-train.c, 8978 , 2014-04-01
libsvm-3.18\svm.cpp, 64702 , 2014-04-01
libsvm-3.18\svm.def, 477 , 2014-04-01
libsvm-3.18\svm.h, 3382 , 2014-04-01
libsvm-3.18\tools, 0 , 2014-07-22
libsvm-3.18\tools\checkdata.py, 2479 , 2014-04-01
libsvm-3.18\tools\easy.py, 2699 , 2014-04-01
libsvm-3.18\tools\grid.py, 15304 , 2014-04-01
libsvm-3.18\tools\README, 7033 , 2014-04-01
libsvm-3.18\tools\subset.py, 3202 , 2014-04-01
libsvm-3.18\windows, 0 , 2014-07-22
libsvm-3.18\windows\libsvm.dll, 160256 , 2014-04-01
libsvm-3.18\windows\libsvmread.mexw64, 11264 , 2014-04-01
libsvm-3.18\windows\libsvmwrite.mexw64, 10240 , 2014-04-01
libsvm-3.18\windows\svm-predict.exe, 125952 , 2014-04-01
libsvm-3.18\windows\svm-scale.exe, 81408 , 2014-04-01
libsvm-3.18\windows\svm-toy.exe, 141312 , 2014-04-01
libsvm-3.18\windows\svm-train.exe, 155648 , 2014-04-01
libsvm-3.18\windows\svmpredict.mexw64, 25600 , 2014-04-01
libsvm-3.18\windows\svmtrain.mexw64, 64512 , 2014-04-01

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  • ST
    说明:  广义S变换,具有良好的分析特性和局部的时频的特性,而谱白化和反褶积也是高分辨处理中的一种有效的频率补偿手段,本文利用他们的他们的各自优点,使二者结合起来,该方法对地震信号用广义S变换分解,进行频率补偿再进行重构,得到高分辨率时间信号。  理论模型试算和实际地震处理结果证明了该方法的正确性和有效性。  关键词:广义S变换,谱白化,高分辨处理(Generalized S transformation (GST) has good analyzing feature and good Time-frequency localization,. spectrum whitening and deconvolution is an Effective tool for frequency compensation , Utilizing both their advantages , The method first conducts GST decomposition to seismic data,. doing high frequency compensation and then reconstruction to get high resolution seismic to get a high-resolution time signal. Theoretic modeling and field seismic data processing results has proved this method corrected and effective . )
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    积分:1
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    有很多频谱细化的程序 大家一起学习!!都是来自论坛上的贴子 很好用 有很大的启发性
    2009-07-02 14:28:15下载
    积分:1
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    说明:  基于MATLAB_Simulink的扩频通信系统仿真及抗干扰研究 (Spread Spectrum Communication System Based on MATLAB_Simulink simulation and interference studies)
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    说明:  matlab利用maple的强大的函数功能实现ELGamla算法,是matlab的效率更高。(matlab function using maple powerful features to achieve ELGamla algorithm is more efficient matlab.)
    2011-04-17 00:33:02下载
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    2018-04-21 10:42:14下载
    积分:1
  • STFT0629
    用短时傅立叶变换对信号进行时频分析,并有频谱图随着窗的大小进行的对比。(Using short-time Fourier transform of the signal time-frequency analysis and frequency spectrum as the window size of the contrast.)
    2008-07-19 17:03:12下载
    积分:1
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