Programmer Guide/Command Reference/EVAL/optmm: Difference between revisions

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:*The smoothed output is computed as follows:
:*The smoothed output is computed as follows:
::<math>r[i]=\sum_{j=-M}^M \sum_{k=-N}^N a[i+j,N+k]*w[M+j,N+k]</math>
::<math>r[i]=\sum_{j=-M}^M \sum_{k=-N}^N a[i+j,N+k]*w[M+j,N+k]</math>
::note: for all indices <code>i+j<0</code> or <code>i+j>=nrow(''a'')</code> a[i+j] equals '''0'''.
::with: <code>i=0..nrow(''a'')-1</code>; <code>''a''[i+j]=0 if <code>i+j<0</code> or <code>i+j>=nrow(''a'')</code>


;Result: The vector ''r'' with the length <code>nrow(''a'')</code>, containing the smooth filter spectrum.
;Result: The vector ''r'' with the length <code>nrow(''a'')</code>, containing the smooth filter spectrum.

Revision as of 14:28, 20 April 2011

Smooth multiplier matrix using a two dimensional convolution. The function optmm</comp> was especially implemented for the script application MulAc.

Usage
optmm(mflag, a, w)
mflag
selects the method used to modify the multiplier matrix; currently only the method mflag=0 is implemented
a
The multiplier matrix. Each row a[i] contains one linear filter spectrum to be applied to a signal.
w
The smoothing matrix, containg a two dimensional a smoothing function.
Description
  • nrow(w) = 2M+1 and nrow(a) >> M
  • ncol(w) = 2N+1 and ncol(w) = ncol(a)
  • The matrix w contains the weighting function, with the maximum at w[M,N] and which should be symetrical in both dimensions.
w[M-i,N-j]=w[M-i,N+j]=w[M+i,N-j]=w[M+i,N+j]; with: i=1..M, j=1..N
  • The smoothed output is computed as follows:
{\displaystyle r[i]=\sum _{j=-M}^{M}\sum _{k=-N}^{N}a[i+j,N+k]*w[M+j,N+k]}
with: i=0..nrow(a)-1; a[i+j]=0 if i+j<0 or i+j>=nrow(a)
Result
The vector r with the length nrow(a), containing the smooth filter spectrum.
See also
hcomb, cvphase, script application MulAc

<function list>

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