section f of routines in filter.i

functions in filter.i - f

fft_good


    fft_good(n)  


returns the smallest number of the form 2^x*3^y*5^z greater  
than or equal to n.  An fft of this length will be much faster  
than a number with larger prime factors; the speed difference  
can be an order of magnitude or more.  
For n>100, the worst cases result in a little over a 11% increase  
in n; for n>1000, the worst are a bit over 6%; still larger n are  
better yet.  The median increase for n<=10000 is about 1.5%.

SEE ALSO: filter, fil_analyze

fil_normalize


    fil_normalize  


  
     Interpreted function, defined at i/filter.i   line 473

fil_poly


    fil_poly(c, x)  


return c(1) + c(2)*x + c(3)*x^2 + c(4)*x^3 + ...  
Interpreted function, defined at i/filter.i   line 115

fil_response


    fil_response(filt, w)  


return the complex response of FILT at the frequencies W.  
The frequency scale for W depends on how FILT has been scaled;  
filters are rational functions in W.  
The to_db and to_phase functions may be useful for extracting  
the attenuation and phase parts of the complex response.  
Interpreted function, defined at i/filter.i   line 72

SEE ALSO: filter, fil_butter, fil_bessel, fil_cheby1, fil_cheby2, fil_delay,
to_db, to_phase

filter


    filter(filt, dt, signal)  


apply the filter FILT to the input SIGNAL, which is sampled  
at times spaced by DT.  The filter is assumed to be normalized  
to an angular frequency (e.g.- radians per second), unless  
DT<0, in which case FILT is assumed to be normalized to a  
circular frequency (e.g.- Hz or GHz).  
The result will have the same length as SIGNAL; be sure to pad  
SIGNAL if you need the response to go beyond that time, or  
you can use the pad=n keyword to force the returned result to  
have N samples more than SIGNAL.  
If the shift= keyword is non-nil and non-0, then the result  
is shifted backward in time by the filter group delay at  
zero frequency.  
The impulse response of the FILT is also assumed to be shorter  
than the duration of signal, and SIGNAL is assumed to be sampled  
finely enough to resolve the FILT impulse response.  
FILT is an array of double, which represents a filter with  
a particular finite list of zeroes and poles.  See the specific  
functions to construct filters from poles and zeroes (fil_make),  
or classic Bessel, Butterworth, Chebyshev, inverse Chebyshev, or  
Cauer (elliptic) designs.  With fil_analyze, you can find the  
poles and zeroes of a FILT.  The format for FILT is:  
FILT is an array of double with the following meanings:  
  FILT(1) = np = number of poles  (integer >= 0)  
  FILT(2) = nz = number of zeroes (integer >= 0)  
  FILT(3) = reserved  
  FILT(4:4+nz) = coefficients for numerator  
            = [a0, a1, a2, a3, ..., anz]  
  FILT(5+nz:4+nz+np) = coefficents for denominator (if np>0)  
            = [b1, b2, b3, ..., bnp]  
The Laplace transform (s-transform) of the filter response is  
  L[FILT] = (a0 + a1*s + a2*s^2 + a3*s^3 + ...) /  
            ( 1 + b1*s + b2*s^2 + b3*s^3 + ...)  
Interpreted function, defined at i/filter.i   line 8

SEE ALSO: filter, fil_bessel, fil_butter, fil_cheby1, fil_cheby2, fil_cauer,
fil_response, fil_make, fil_analyze, to_db, to_phase