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function y = rms(f,varargin)
%-*- texinfo -*-
%@deftypefn {Function} rms
%@verbatim
%RMS RMS value of signal
% Usage: y = rms(f);
% y = rms(f,...);
%
% RMS(f) computes the RMS (Root Mean Square) value of a finite sampled
% signal sampled at a uniform sampling rate. This is a vector norm
% equal to the l^2 averaged by the length of the signal.
%
% If the input is a matrix or ND-array, the RMS is computed along the
% first (non-singleton) dimension, and a vector of values is returned.
%
% The RMS value of a signal x of length N is computed by
%
% N
% rms(f) = 1/sqrt(N) ( sum |f(n)|^2 )^(1/2)
% n=1
%
% RMS takes the following flags at the end of the line of input
% parameters:
%
% 'ac' Consider only the AC component of the signal (i.e. the mean is
% removed).
%
% 'dim',d Work along specified dimension. The default value of []
% means to work along the first non-singleton one.
%
%@end verbatim
%@strong{Url}: @url{http://ltfat.github.io/doc/sigproc/rms.html}
%@end deftypefn
% Copyright (C) 2005-2016 Peter L. Soendergaard <peter@sonderport.dk>.
% This file is part of LTFAT version 2.3.1
%
% 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/>.
% AUTHOR : Peter L. Soendergaard
%% ------ Checking of input parameters ---------
if ~isnumeric(f)
error('%s: Input must be numerical.',upper(mfilename));
end;
if nargin<1
error('%s: Too few input parameters.',upper(mfilename));
end;
definput.keyvals.dim=[];
definput.flags.mean={'noac','ac'};
[flags,kv]=ltfatarghelper({},definput,varargin);
%% ------ Computation --------------------------
% It is better to use 'norm' instead of explicitly summing the squares, as
% norm (hopefully) attempts to avoid numerical overflow.
[f,L,Ls,W,dim,permutedsize,order]=assert_sigreshape_pre(f,[],kv.dim, ...
upper(mfilename));
permutedsize(1)=1;
y=zeros(permutedsize);
if flags.do_ac
for ii=1:W
y(1,ii) = norm(f(:,ii)-mean(f(:,ii)))/sqrt(L);
end;
else
for ii=1:W
y(1,ii)=norm(f(:,ii))/sqrt(L);
end;
end;
y=assert_sigreshape_post(y,kv.dim,permutedsize,order);
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