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view extra/tsa/inst/lpc.m @ 12579:a7796f4b9837 octave-forge
fix documentation [bugs #44673]
author | schloegl |
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date | Thu, 02 Apr 2015 09:57:46 +0000 |
parents | 430712382527 |
children | b6eace8bc216 |
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function [A] = lpc(Y,P,mode); % LPC Linear prediction coefficients % The Burg-method is used to estimate the prediction coefficients % % A = lpc(X [,P]) finds the coefficients A=[ 1 A(2) ... A(N+1) ], % of an Pth order forward linear predictor % % Xp(n) = -A(2)*X(n-1) - A(3)*X(n-2) - ... - A(N+1)*X(n-P) % % such that the sum of the squares of the errors % % err(n) = X(n) - Xp(n) % % is minimized. X can be a vector or a matrix. If X is a matrix % containing a separate signal in each column, LPC returns a model % estimate for each column in the rows of A. N specifies the order % of the polynomial A(z). % % If you do not specify a value for P, LPC uses a default P = length(X)-1. % % % see also ACOVF ACORF AR2POLY RC2AR DURLEV SUMSKIPNAN LATTICE % % REFERENCE(S): % J.P. Burg, "Maximum Entropy Spectral Analysis" Proc. 37th Meeting of the Society of Exp. Geophysiscists, Oklahoma City, OK 1967 % J.P. Burg, "Maximum Entropy Spectral Analysis" PhD-thesis, Dept. of Geophysics, Stanford University, Stanford, CA. 1975. % P.J. Brockwell and R. A. Davis "Time Series: Theory and Methods", 2nd ed. Springer, 1991. % S. Haykin "Adaptive Filter Theory" 3rd ed. Prentice Hall, 1996. % M.B. Priestley "Spectral Analysis and Time Series" Academic Press, 1981. % W.S. Wei "Time Series Analysis" Addison Wesley, 1990. % $Id$ % Copyright (C) 1996-2002,2008 by Alois Schloegl <a.schloegl@ieee.org> % This is part of the TSA-toolbox. See also % http://pub.ist.ac.at/~schloegl/matlab/tsa/ % % This program is free software: you can redistribute it and/or modify % it under the terms of the GNU General Public License as published by % the Free Software Foundation, either version 3 of the License, or % (at your option) any later version. % % This program is distributed in the hope that it will be useful, % but WITHOUT ANY WARRANTY; without even the implied warranty of % MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the % GNU General Public License for more details. % % You should have received a copy of the GNU General Public License % along with this program. If not, see <http://www.gnu.org/licenses/>. [yr,yc] = size(Y); if yr < yc, fprintf(2,'Warning LCP: data vector Y must be a column not a row vector\n'); end; if nargin < 2, P = yr-1; end; % you can use any of the following routines. % the lattice methods are preferable for stochastic time series. % but can fail for deterministic signals see: % http://sourceforge.net/mailarchive/message.php?msg_name=20080516115110.GB20642%40localhost % [AR,RC,PE] = lattice(Y.',P); % Burg method % [AR,RC,PE] = lattice(Y.',P,'GEOL'); % geometric lattice [AR,RC,PE] = durlev(acovf(Y.',P)); % Yule-Walker A = ar2poly(AR);