--- a/extra/tsa/README.TXT	Wed Apr 10 12:03:09 2002 +0000
+++ b/extra/tsa/README.TXT	Wed Apr 10 12:15:24 2002 +0000
@@ -9,7 +9,7 @@
 It includes
 - Stochastic Signal processing 
 - Autoregressive Model Identification 
-- adaptive autoregressive modelling 
+- adaptive autoregressive modelling 
using Kalman filtering
 - multivariate autoregressive modelling 
 - maximum entropy spectral estimation 
 - matched (inverse) filter design
@@ -46,6 +46,6 @@
 
 Copyright (c) 1996-2002 by Alois Schloegl 
 E-Mail:   a.schloegl@ieee.org
-WWW:      http://www-dpmi.tu-graz.ac.at/~schloegl/matlab/tsa
+WWW:      http://www.dpmi.tu-graz.ac.at/~schloegl/matlab/tsa
 
 

--- a/extra/tsa/aar.m	Wed Apr 10 12:03:09 2002 +0000
+++ b/extra/tsa/aar.m	Wed Apr 10 12:15:24 2002 +0000
@@ -1,7 +1,7 @@
 function [a,e,REV,TOC,CPUTIME,ESU] = aar(y, Mode, arg3, arg4, arg5, arg6, arg7, arg8, arg9); 
+% Calculates adaptive autoregressive (AAR) and adaptive autoregressive moving average estimates (AARMA)
+% of real-valued data series using Kalman filter algorithm.
 % [a,e,REV] = aar(y, mode, MOP, UC, a0, A); 
-% Calculates adaptive autoregressive (AAR) and adaptive autoregressive moving average estimates (AARMA)
-% of real-valued data series with Kalman filter algorithm.
 %
 % The AAR process is described as following  
 %       y(k) - a(k,1)*y(t-1) -...- a(k,p)*y(t-p) = e(k);

--- a/extra/tsa/acorf.m	Wed Apr 10 12:03:09 2002 +0000
+++ b/extra/tsa/acorf.m	Wed Apr 10 12:15:24 2002 +0000
@@ -1,5 +1,4 @@
 function [AUTOCOV,stderr,lpq,qpval] = acorf(Z,N);
-%  Normalized Autocorrelation function  
 %  Calculates autocorrelations for multiple data series.
 %  Missing values in Z (NaN) are considered. 
 %  Also calculates Ljung-Box Q stats and p-values.

--- a/extra/tsa/arfit2.m	Wed Apr 10 12:03:09 2002 +0000
+++ b/extra/tsa/arfit2.m	Wed Apr 10 12:15:24 2002 +0000
@@ -1,11 +1,11 @@
 function [w, MAR, C, sbc, fpe, th]=arfit(Y, pmin, pmax, selector, no_const)
 % ARFIT2 estimates multivariate autoregressive parameters
-%   using MDURLEV wiht the Nuttall-Strand method [1,2]. 
+%   using MDURLEV with the Nuttall-Strand method [1,2]. 
 % ARFIT2 is included for combatibility reasons to ARFIT [3]
 %  
 %  [w, A, C, sbc, fpe] = arfit2(v, pmin, pmax, selector, no_const)
 %
-% see also: ARFIT, MDURLEV
+% see also: ARFIT, MVAR
 %
 % REFERENCES:
 %  [1] M.S. Kay "Modern Spectral Estimation" Prentice Hall, 1988. 

--- a/extra/tsa/flix.m	Wed Apr 10 12:03:09 2002 +0000
+++ b/extra/tsa/flix.m	Wed Apr 10 12:15:24 2002 +0000
@@ -1,5 +1,5 @@
 function Y=flix(D,x)
-% FLIX floating point index
+% floating point index - interpolates data in case of non-integer indices
 %
 % Y=flix(D,x)
 %   FLIX returns Y=D(x) if x is an integer 

--- a/extra/tsa/invest0.m	Wed Apr 10 12:03:09 2002 +0000
+++ b/extra/tsa/invest0.m	Wed Apr 10 12:15:24 2002 +0000
@@ -1,5 +1,5 @@
 function [AutoCov,AutoCorr,MX,E,NC]=invest0(Y,Pmax,Mode);
-% First Investigation of a signal (time series)
+% First Investigation of a signal (time series)
 - automated part
 % [AutoCov,AutoCorr,ARPMX,E,ACFsd,NC]=invest0(Y,Pmax);
 %
 % [AutoCov,AutoCorr,ARPMX,E,ACFsd,NC]=invest0(AutoCov,Pmax,Mode);

--- a/extra/tsa/invest1.m	Wed Apr 10 12:03:09 2002 +0000
+++ b/extra/tsa/invest1.m	Wed Apr 10 12:15:24 2002 +0000
@@ -1,5 +1,5 @@
 function [AutoCov,AutoCorr,ARPMX,E,C,s]=invest1(Y,Pmax,D);
-% First Investigation of a signal (time series)
+% First Investigation of a signal (time series)
 - interactive
 % [AutoCov,AutoCorr,ARPMX,E,CRITERIA,MOPS]=invest1(Y,Pmax,show);
 %
 % Y	time series

--- a/extra/tsa/lattice.m	Wed Apr 10 12:03:09 2002 +0000
+++ b/extra/tsa/lattice.m	Wed Apr 10 12:15:24 2002 +0000
@@ -1,8 +1,7 @@
  function [MX,PE,arg3] = lattice(Y,lc,Mode);
-% Estimates AR(p) model parameter with lattice algorithm 
-% by Burg (1968) for multiple channels. 
-% LATTICE.M can handle missing values (NaN), if you have the 
-% NaN-tools http://www.dpmi.tu-graz.ac.at/~schloegl/matlab/NaN/
+% Estimates AR(p) model parameter with lattice algorithm (Burg 1968) 
+% for multiple channels. 
+% If you have the 
NaN-tools, LATTICE.M can handle missing values (NaN), 
 %
 % [...] = lattice(y [,Pmax [,Mode]]);
 %

--- a/extra/tsa/mvar.m	Wed Apr 10 12:03:09 2002 +0000
+++ b/extra/tsa/mvar.m	Wed Apr 10 12:15:24 2002 +0000
@@ -1,7 +1,6 @@
 function [ARF,RCF,PE,DC,varargout] = mvar(Y, Pmax, Mode);
+% estimates a multivariate AR(p) model parameter
 % function  [MAR,RC,PE] = mvar(Y [,Pmax]);
-% estimates a multivariate AR(p) model parameter by solving the
-% multivariate Yule-Walker with various methods [2]
 %
 %  INPUT:
 % ACF	Autocorrelation function from lag=[0:p]

--- a/extra/tsa/poly2rc.m	Wed Apr 10 12:03:09 2002 +0000
+++ b/extra/tsa/poly2rc.m	Wed Apr 10 12:15:24 2002 +0000
@@ -1,9 +1,7 @@
 function [RC,r0] = poly2rc(a,efinal);
-%
+%
 converts AR-polynomial into reflection coefficients
 % [k,r0] = poly2rc(a [,efinal])
 %
-% requires TSA-tb >Ver 2.70
-%
 % see also ACOVF ACORF AR2RC RC2AR DURLEV AC2POLY, POLY2RC, RC2POLY, RC2AC, AC2RC, POLY2AC
 % 
 

--- a/extra/tsa/rc2ac.m	Wed Apr 10 12:03:09 2002 +0000
+++ b/extra/tsa/rc2ac.m	Wed Apr 10 12:15:24 2002 +0000
@@ -2,9 +2,6 @@
 % 
converts reflection coefficients to autocorrelation sequence
 % [R] = rc2ac(K,R0);
 %
-%
-% requires TSA-tb >Ver 2.70
-%
 % see also ACOVF ACORF AR2RC RC2AR DURLEV AC2POLY, POLY2RC, RC2POLY, RC2AC, AC2RC, POLY2AC
 % 
 

--- a/extra/tsa/rc2ar.m	Wed Apr 10 12:03:09 2002 +0000
+++ b/extra/tsa/rc2ar.m	Wed Apr 10 12:15:24 2002 +0000
@@ -1,6 +1,6 @@
 function [MX,res,arg3,acf] = rc2ar(rc);
 % converts reflection coefficients into autoregressive parameters
-% with the Durbin-Levinson recursion for multiple channels
+% uses the Durbin-Levinson recursion for multiple channels
 % function  [AR,RC,PE,ACF] = rc2ar(RC);
 % function  [MX,PE] = rc2ar(RC);
 %
@@ -18,7 +18,7 @@
 % All input and output parameters are organized in rows, one row 
 % corresponds to the parameters of one channel
 %
-% see also ACOVF ACORF DURLEV IDURLEV PARCOR YUWA 
+% see also ACOVF ACORF DURLEV AR2RC 
 % 
 % REFERENCES:
 %  P.J. Brockwell and R. A. Davis "Time Series: Theory and Methods", 2nd ed. Springer, 1991.

--- a/extra/tsa/rc2poly.m	Wed Apr 10 12:03:09 2002 +0000
+++ b/extra/tsa/rc2poly.m	Wed Apr 10 12:15:24 2002 +0000
@@ -2,9 +2,6 @@
 %
 converts reflection coefficients into an AR-polynomial
 % [a,efinal] = rc2poly(K)
 %
-%
-% requires TSA-tb >Ver 2.70
-%
 % see also ACOVF ACORF AR2RC RC2AR DURLEV AC2POLY, POLY2RC, RC2POLY, RC2AC, AC2RC, POLY2AC
 % 
 

--- a/extra/tsa/sbispec.m	Wed Apr 10 12:03:09 2002 +0000
+++ b/extra/tsa/sbispec.m	Wed Apr 10 12:15:24 2002 +0000
@@ -1,5 +1,5 @@
 function sbispec(BISPEC)
-% SBISPEC Show BISPECTRUM 
+% SBISPEC show BISPECTRUM 
 
 %	Version 0.23
 %	last revision 21.03.1998

--- a/extra/tsa/sinvest1.m	Wed Apr 10 12:03:09 2002 +0000
+++ b/extra/tsa/sinvest1.m	Wed Apr 10 12:15:24 2002 +0000
@@ -1,8 +1,7 @@
 %SINVEST1 shows the parameters of a time series calculated by INVEST1
 % only called by INVEST1
 
-%       Version 2.90
-%       24.03.2002
+%       Version 2.90
,        24.03.2002
 %	Copyright (c) 1998-2002 by  Alois Schloegl
 %	a.schloegl@ieee.org	
 

--- a/extra/tsa/ucp.m	Wed Apr 10 12:03:09 2002 +0000
+++ b/extra/tsa/ucp.m	Wed Apr 10 12:15:24 2002 +0000
@@ -1,5 +1,5 @@
 function b=ucp(c)
-%UCP(C)	tests if the polynomial C is a Unit-Circle-Polynomial.
+% UCP(C) tests if the polynomial C is a Unit-Circle-Polynomial.
 %	It tests if all roots lie inside the unit circle like
 %       B=ucp(C) does the same as
 %	B=all(abs(roots(C))<1) but much faster.

--- a/extra/tsa/y2res.m	Wed Apr 10 12:03:09 2002 +0000
+++ b/extra/tsa/y2res.m	Wed Apr 10 12:15:24 2002 +0000
@@ -1,5 +1,5 @@
 function [R,MU,SD2,EM3,EM4,Max,Min,I,th1prm]=y2res(Y)
-% Evaluates data series
+% Evaluates basic statistics of a data series
 % [N,MU,SD2,EM3,EM4,Max,Min,I]=y2res(y)
 % 
 % OUTPUT:
@@ -18,8 +18,7 @@
 % [1] http://www.itl.nist.gov/
 % [2] http://mathworld.wolfram.com/
 
-%	Version 2.90
-%	last revision 05.04.2002
+%	Version 2.90
	last revision 10.04.2002
 %	Copyright (c) 1996-2002 by Alois Schloegl
 %	e-mail: a.schloegl@ieee.org