HOSP-matlab
所属分类：matlab编程
开发工具：matlab
文件大小：121KB
下载次数：65
上传日期：2011-08-16 14:59:22
上 传 者：
vipkoala
说明： 这是一份高阶统计量的资料，有相关的程序，目前高阶统计量是研究的热门话题，对于地震子波的高精度提取有重要意义。
(This is a higher-order statistics of the data full of relevant procedures,and at present higher-order statistics is a hot topic which is very important and significant for high-precision seismic wavelet extraction.)
文件列表:
高阶统计量\hosa\ARMAQS.M (4452, 2011-06-09)
高阶统计量\hosa\ARMARTS.M (2862, 2011-06-09)
高阶统计量\hosa\ARMASYN.M (4044, 2011-06-09)
高阶统计量\hosa\ARORDER.M (4165, 2011-06-09)
高阶统计量\hosa\ARRCEST.M (4034, 2011-06-09)
高阶统计量\hosa\BICEPS.M (5449, 2011-06-09)
高阶统计量\hosa\BICEPSF.M (5139, 2011-06-09)
高阶统计量\hosa\BICOHER.M (4206, 2011-06-09)
高阶统计量\hosa\BICOHERX.M (4717, 2011-06-09)
高阶统计量\hosa\BISPECD.M (5854, 2011-06-09)
高阶统计量\hosa\BISPECDX.M (6508, 2011-06-09)
高阶统计量\hosa\BISPECI.M (5243, 2011-06-09)
高阶统计量\hosa\BISPECT.M (1974, 2011-06-09)
高阶统计量\hosa\bispest.asv (5867, 2011-06-09)
高阶统计量\hosa\CONTENTS.M (4939, 2011-06-09)
高阶统计量\hosa\CUM2EST.M (2069, 2011-06-09)
高阶统计量\hosa\CUM2X.M (3133, 2011-06-09)
高阶统计量\hosa\CUM3EST.M (2902, 2011-06-09)
高阶统计量\hosa\CUM3X.M (3611, 2011-06-09)
高阶统计量\hosa\CUM4EST.M (4463, 2011-06-09)
高阶统计量\hosa\CUM4X.M (5704, 2011-06-09)
高阶统计量\hosa\CUMEST.M (2764, 2011-06-09)
高阶统计量\hosa\CUMTRUE.M (4516, 2011-06-09)
高阶统计量\hosa\DOA.M (5955, 2011-06-09)
高阶统计量\hosa\DOAGEN.M (5605, 2011-06-09)
高阶统计量\hosa\GLSTAT.M (8677, 2011-06-09)
高阶统计量\hosa\HARMEST.M (6512, 2011-06-09)
高阶统计量\hosa\HARMGEN.M (3757, 2011-06-09)
高阶统计量\hosa\HOSAHELP.M (4260, 2011-06-09)
高阶统计量\hosa\HOSAVER.M (706, 2011-06-09)
高阶统计量\hosa\HPRONY.M (3194, 2011-06-09)
高阶统计量\hosa\INFO.XML (402, 2011-06-09)
高阶统计量\hosa\IVCAL.M (2118, 2011-06-09)
高阶统计量\hosa\MAEST.M (3374, 2011-06-09)
高阶统计量\hosa\MAORDER.M (2915, 2011-06-09)
高阶统计量\hosa\MATUL.M (2840, 2011-06-09)
高阶统计量\hosa\NLGEN.M (2269, 2011-06-09)
高阶统计量\hosa\NLPOW.M (3912, 2011-06-09)
高阶统计量\hosa\NLTICK.M (4611, 2011-06-09)
高阶统计量\hosa\PICKPEAK.M (2721, 2011-06-09)
... ...
% README file for the HOSA Toolbox.
% Version 2.0.3 (R12 Compliant) 27 Dec 2000
%
% Note: There have been no changes in Toolbox functionality.
% *********************************************************************
% Bug fixes for version 2.0.3:
%
% 1) CUM4X - Corrected conjugation errors related to the computation of
% R_wy, R_zy and M_yx.
%
% 2) TDE - Corrected a size error when the 'svdflag' input argument was
% used.
%
% *********************************************************************
% The HOSA Manual:
%
% The classification example in the Case Studies section of the Higher
% Order Spectral Analysis Toolbox manual does not define x and y.
% Users cannot run the example because they do not have the two
% underwater acoustic signals.
% *********************************************************************
% Changes to the Toolbox for version 2.0.2:
%
% 1) There have been no changes in Toolbox functionality. Several
% of the demo M-files have been modified. In particular, each demo
% can be invoked separately without going through the HOSADEM or
% HOSADEMO functions.
%
% 2) Command-line demos will now plot to only one figure window.
%
% 3) Case-study demo figures will be closed upon completion of each
% case study.
%
% 4) The matul function has been changed to correct a bug.
% The function now produces the correct coefficient matrix
% based on the Matsuoka-Ulrych paper.
%
% 5) The harmest, doa, tde, and qpctor functions have been modified
% to validate user-entered order.
%
% 6) The hprony function has been modified to fix incompatibilities
% with the toeplitz function.
%
% 7) Several other minor changes (i.e. add grid lines)
%
% *********************************************************************
% The HOSA Manual:
%
% The classification example in the Case Studies section of the Higher
% Order Spectral Analysis Toolbox manual does not define x and y.
% Users cannot run the example because they do not have the two
% underwater acoustic signals.
%**********************************************************************
%
% Changes to the HOSA Manual
% A bug in routine glstat.m has been fixed; this leads to
% changes in the output of glstat.m; HOSA manual pages should
% be corrected as shown below (none of the interpretations change)
%
% On p 1-21,1-22:
%
% glstat(g,0.51,256)
% Test statistic for Gaussianity is 22.179 with df = 48, Pfa = 0.9995
% Linearity test:
% R (estimated) = 0.88819, lambda = 0.68932, R (theory) = 2.9288, N = 14
%
% glstat(u,0.51,256)
% Test statistic for Gaussianity is 17.4885 with df = 48, Pfa = 1
% Linearity test:
% R (estimated) = 0.72383, lambda = 0.51704, R (theory) = 2.7453, N = 14
%
% glstat(e,0.51,256)
% Test statistic for Gaussianity is 253.3529 with df = 48, Pfa = 0
% Linearity test:
% R (estimated) = 7.8894, lambda = 9.4555, R (theory) = 8.4655, N = 14
%
% glstat(x,0.51,256)
% Test statistic for Gaussianity is 277.5194 with df = 48, Pfa = 0
% Linearity test:
% R (estimated) = 6.7513, lambda = 10.6519, R (theory) = 8.968, N = 14
%
% glstat(z,0.51,256)
% Test statistic for Gaussianity is 12***0.0657 with df = 48, Pfa = 0
% Linearity test:
% R (estimated) = 606.9323, lambda = 492.5759, R (theory) = 59.9088, N = 14
%
% glstat(l,0.51,256)
% Test statistic for Gaussianity is 49.931 with df = 48, Pfa = 0.3965
% Linearity test:
% R (estimated) = 2.6047, lambda = 1.8124, R (theory) = 4.0038, N = 14
%
% p 1-96 (sunspot data)
%
% Test statistic for Gaussianity is 357.4639 with df = 60, Pfa = 0
% Linearity test:
% R (estimated) = 14.8592, lambda = 11.0332, R (theory) = 9.1222, N = 16
%
% p 1-*** (sunspot data, differenced)
%
% Test statistic for Gaussianity is 250.1965 with df = 70, Pfa = 0
% Linearity test:
% R (estimated) = 13.5335, lambda = ***449, R (theory) = 7.0433, N = 16
%
%
% p 1-101 (canadian lynx data)
%
% Test statistic for Gaussianity is 196.752 with df = 28, Pfa = 0
% Linearity test:
% R (estimated) = 6.8468, lambda = 11.299, R (theory) = 9.2282, N = 5
%
% p 1-109 (laughter data)
%
% Test statistic for Gaussianity is 71.3231 with df = 48, Pfa = 0.0161
% Linearity test:
% R (estimated) = 2.3216, lambda = 2.376, R (theory) = 4.472, N = 14
%
%**********************************************************************
%
% The classification example in the Case Studies section of the Higher
% Order Spectral Analysis Toolbox manual does not define x and y.
% Users cannot run the example because they do not have the two
% underwater acoustic signals.
%
%
% The laughter example code in the Case Studies section of the doc
% has an error: Change the two lines following
% % --------------------- power spectra and cum-4 spectra
% to
% figure(3), [px2,a21,a22] = harmest(sp,25,12,'biased',512,2);
% figure(4), [px4,a41,a42] = harmest(sp,25, 8,'biased',512,4);
%
%
% The example for estimating cumulants in the Polyspectra and Linear
% Processes section of the manual has a syntax error in its use of the
% contour command. The arguments were in the wrong order. Change the
% line to read as the following and it will work fine.
% subplot(122), contour(-n:n,-n:n,cmat,8)
%
%**********************************************************************
% Copyright (c) 1991-2001 by United Signals & Systems, Inc.
% $Revision: 1.10 $
% A. Swami November 21, 1997
% RESTRICTED RIGHTS LEGEND
% Use, duplication, or disclosure by the Government is subject to
% restrictions as set forth in subparagraph (c) (1) (ii) of the
% Rights in Technical Data and Computer Software clause of DFARS
% 252.227-7013.
% Manufacturer: United Signals & Systems, Inc., P.O. Box 2374,
% Culver City, California 90231.
%
% This material may be reproduced by or for the U.S. Government pursuant
% to the copyright license under the clause at DFARS 252.227-7013.
disp('HOSA Toolbox Version 2.0.3 (R12 compliant) 27 Dec 2000')
disp('Press any key to see readme file'),pause
clc, help readme
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