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# maxfilt

## PURPOSE

MAXFILT find max of an exponentially weighted sliding window [Y,K,Y0]=(X,F,nn,D,X0)

## SYNOPSIS

function [y,k,y0]=maxfilt(x,f,n,d,x0)

## DESCRIPTION

```MAXFILT find max of an exponentially weighted sliding window  [Y,K,Y0]=(X,F,nn,D,X0)

Usage: (1) y=maxfilt(x)   % maximum filter along first non-singleton dimension
(2) y=maxfilt(x,0.95) % use a forgetting factor of 0.95 (= time const of -1/log(0.95)=19.5 samples)
(3) Two equivalent methods (i.e. you can process x in chunks):
y=maxfilt([u v]);      [yu,ku,x0)=maxfilt(u);
yv=maxfilt(v,[],[],[],x0);
y=[yu yv];

Inputs:  X  Vector or matrix of input data
F  exponential forgetting factor in the range 0 (very forgetful) to 1 (no forgetting)
F=exp(-1/T) gives a time constant of T samples [default = 1]
n  Length of sliding window [default = Inf (equivalent to [])]
D  Dimension for work along [default = first non-singleton dimension]
X0  Initial values placed in front of the X data

Outputs: Y  Output matrix - same size as X
K  Index array: Y=X(K). (Note that these value may be <=0 if input X0 is present)
Y0  Last nn-1 values (used to initialize a subsequent call to
maxfilt()) (or last output if n=Inf)

This routine calaulates y(p)=max(f^r*x(p-r), r=0:n-1) where x(r)=-inf for r<1
y=x(k) on output```

## CROSS-REFERENCE INFORMATION

This function calls:
This function is called by:
• activlev ACTIVLEV Measure active speech level as in ITU-T P.56 [LEV,AF,FSO]=(sp,FS,MODE)
• dypsa DYPSA Derive glottal closure instances from speech [gci,goi] = (s,fs)
• v_ppmvu V_PPMVU calculate PPM, VU or EBU level of an audio signal [V,FX,FX1]=(X,FSX,M)

## SOURCE CODE

```0001 function [y,k,y0]=maxfilt(x,f,n,d,x0)
0002 %MAXFILT find max of an exponentially weighted sliding window  [Y,K,Y0]=(X,F,nn,D,X0)
0003 %
0004 % Usage: (1) y=maxfilt(x)   % maximum filter along first non-singleton dimension
0005 %        (2) y=maxfilt(x,0.95) % use a forgetting factor of 0.95 (= time const of -1/log(0.95)=19.5 samples)
0006 %        (3) Two equivalent methods (i.e. you can process x in chunks):
0007 %                 y=maxfilt([u v]);      [yu,ku,x0)=maxfilt(u);
0008 %                                        yv=maxfilt(v,[],[],[],x0);
0009 %                                        y=[yu yv];
0010 %
0011 % Inputs:  X  Vector or matrix of input data
0012 %          F  exponential forgetting factor in the range 0 (very forgetful) to 1 (no forgetting)
0013 %             F=exp(-1/T) gives a time constant of T samples [default = 1]
0014 %          n  Length of sliding window [default = Inf (equivalent to [])]
0015 %          D  Dimension for work along [default = first non-singleton dimension]
0016 %         X0  Initial values placed in front of the X data
0017 %
0018 % Outputs: Y  Output matrix - same size as X
0019 %          K  Index array: Y=X(K). (Note that these value may be <=0 if input X0 is present)
0020 %         Y0  Last nn-1 values (used to initialize a subsequent call to
0021 %             maxfilt()) (or last output if n=Inf)
0022 %
0023 % This routine calaulates y(p)=max(f^r*x(p-r), r=0:n-1) where x(r)=-inf for r<1
0024 % y=x(k) on output
0025
0026 % Example: find all peaks in x that are not exceeded within +-w samples
0027 % w=4;m=100;x=rand(m,1);[y,k]=maxfilt(x,1,2*w+1);p=find(((1:m)-k)==w);plot(1:m,x,'-',p-w,x(p-w),'+')
0028
0029 % Bugs/suggestion
0030 % (1) if n<0 then centre filter support of the current sample (or make it +-n)
0031
0032 %      Copyright (C) Mike Brookes 2003-2014
0033 %      Version: \$Id: maxfilt.m 10140 2017-09-27 09:30:06Z dmb \$
0034 %
0035 %   VOICEBOX is a MATLAB toolbox for speech processing.
0037 %
0038 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
0039 %   This program is free software; you can redistribute it and/or modify
0041 %   the Free Software Foundation; either version 2 of the License, or
0042 %   (at your option) any later version.
0043 %
0044 %   This program is distributed in the hope that it will be useful,
0045 %   but WITHOUT ANY WARRANTY; without even the implied warranty of
0046 %   MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
0047 %   GNU General Public License for more details.
0048 %
0049 %   You can obtain a copy of the GNU General Public License from
0050 %   http://www.gnu.org/copyleft/gpl.html or by writing to
0051 %   Free Software Foundation, Inc.,675 Mass Ave, Cambridge, MA 02139, USA.
0052 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
0053
0054 s=size(x);
0055 if nargin<4 || isempty(d)           % if d is unspecified
0056     d=find(s>1,1);                  % find first non-singleton dimension
0057     if isempty(d)
0058         d=1;                        % else defailt to dimension 1
0059     end
0060 end
0061 if nargin>4 && numel(x0)>0          % initial values specified
0062     y=shiftdim(cat(d,x0,x),d-1);    % concatenate x0 and x along d
0063     nx0=size(x0,d);                 % number of values added onto front of data
0064 else
0065     y=shiftdim(x,d-1);              % dimension specified, d
0066     nx0=0;                          % no values added onto front of data
0067 end
0068 s=size(y);
0069 s1=s(1);                            % size of active dimension
0070 if nargin<3 || isempty(n)
0071     n0=Inf;                         % default filter support is Inf
0072 else
0073     n0=max(n,1);
0074 end
0075 if nargin<2 || isempty(f)
0076     f=1;
0077 end
0078 nn=n0;
0079 if nargout>2 % we need to output the tail for next time
0080     if n0<Inf
0081         ny0=min(s1,nn-1);
0082     else
0083         ny0=min(s1,1);
0084     end
0085     sy0=s;
0086     sy0(1)=ny0;
0087     if ny0<=0 || n0==Inf
0088         y0=zeros(sy0);
0089     else
0090         y0=reshape(y(1+s1-ny0:end,:),sy0);
0091         y0=shiftdim(y0,ndims(x)-d+1);
0092     end
0093 end
0094 nn=min(nn,s1);         % no point in having nn>s1
0095 k=repmat((1:s1)',[1 s(2:end)]);
0096 if nn>1
0097     j=1;
0098     j2=1;
0099     while j>0
0100         g=f^j;
0101         m=find(y(j+1:s1,:)<=g*y(1:s1-j,:));
0102         m=m+j*fix((m-1)/(s1-j));
0103         y(m+j)=g*y(m);
0104         k(m+j)=k(m);
0105         j2=j2+j;
0106         j=min(j2,nn-j2);                    % j approximately doubles each iteration
0107     end
0108 end
0109 if nargout==0
0110     if nargin<3
0111         x=shiftdim(x);
0112     else
0113         x=shiftdim(x,d-1);
0114     end
0115     ss=min(prod(s(2:end)),5);   % maximum of 5 plots
0116     plot(1:s1,reshape(y(nx0+1:end,1:ss),s1,ss),'-r',1:s1,reshape(x(:,1:ss),s1,ss),':b');
0117 else
0118     if nargout>2 && n0==Inf && ny0==1 % if n0==Inf, we need to save the final output
0119         y0=reshape(y(end,:),sy0);
0120         y0=shiftdim(y0,ndims(x)-d+1);
0121     end
0122     if nx0>0                        % pre-data specified, x0
0123         s(1)=s(1)-nx0;
0124         y=shiftdim(reshape(y(nx0+1:end,:),s),ndims(x)-d+1);
0125         k=shiftdim(reshape(k(nx0+1:end,:),s),ndims(x)-d+1)-nx0;
0126     else                            % no pre-data
0127         y=shiftdim(y,ndims(x)-d+1);
0128         k=shiftdim(k,ndims(x)-d+1);
0129     end
0130 end```

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