[SciPy-User] signal.bilinear question

Warren Weckesser warren.weckesser@enthought....
Mon Aug 30 13:47:17 CDT 2010


Correction to my previous email--I ignored the change of convention for 
the names of the variables in the function call and return values:

Warren Weckesser wrote:
> Neal Becker wrote:
>   
>> Doc is pretty sketchy.
>>   
>>     
>
> Yup.
>   
>> A, B = bilinear (a, b, fs)
>>
>> a, b are numerator, denominator, respectively?
>>   
>>     
>
> No.  a is the denominator, b is the numerator.
>
>   

Actually, you were right.  I didn't pay attention to your change of 
convention for the names of the arguments and return values.  Same for A 
and B below.  (I don't recommend going against the conventional use of 
the names 'a' and 'b'.)


Warren

>> each are polynomials in _descending_ negative powers of s?
>>   
>>     
>
> Yes.
>
>   
>> e.g.: a = a0 + a1 * s**-1 + a2 * s**-2 ...
>>
>> A, B are numerator, denominator, respectively?
>>   
>>     
>
> No--the opposite.
>
>   
>> each are polynomials in descending negative powers of z?
>>   
>>     
>
> Yes.
>
>
> For example, the wikipedia page
>    http://en.wikipedia.org/wiki/Bilinear_transform
> shows that
>
>     1/(1 + (RC)s)
>
> becomes
>
>     (1 + z^-1) / (1+2RC/T) + (1-2RC/T)*z^-1
>
> With RC=3 and T=1, this means
>
>    1/(3*s + 1)
>
> becomes
>
>    (1+z^-1) / (7 - 5*z^-1)
>
> Here's that calculation with bilinear:
>
> -----
> In [32]: b = np.array([1.0])
>
> In [33]: a = np.array([3.0, 1.0])
>
> In [34]: B, A = bilinear(b, a)
>
> In [35]: B, A
> Out[35]: (array([ 0.14285714,  0.14285714]), array([ 1.        , 
> -0.71428571]))
>
> In [36]: 7*B, 7*A
> Out[36]: (array([ 1.,  1.]), array([ 7., -5.]))
> -----
>
> Another example, from the bottom of the 5th page of these notes:
>     www.cs.man.ac.uk/~barry/mydocs/courses/EE4192/LFIL3.pdf
>
> -----
> In [55]: b = np.array([1.0])
>
> In [56]: a = np.array([1.0/0.828**2, np.sqrt(2.)/0.828, 1.0])
>
> In [57]: B, A = bilinear(b, a)
>
> In [58]: B, A
> Out[58]:
> (array([ 0.09755701,  0.19511402,  0.09755701]),
>  array([ 1.        , -0.94326739,  0.33349543]))
>
> In [59]: B/B[0]
> Out[59]: array([ 1.,  2.,  1.])
> -----
>
>
> Warren
>
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