Tuesday, September 19, 2017

filter design - Complex Least Squares Approximation



In the case of frequency domain FIR filter design, the error function given by :


E(ω)=H(ejω)D(ejω)


is a linear function with respect to the unknown filter coefficients h[n]. Hence, the Least Squares frequency domain FIR filter design problem is a linear LS problem which can be solved by computing the solution to a system of linear equations. (from this: Algorithms for the Constrained Design of Digital Filters with Arbitrary Magnitude and Phase Responses ).


I have a three questions :




  • How the error respect the unknown filter coefficient ?




  • Does equation (1) is the same : E(ω)=D(ejω)H(ejω) ?





  • Does this case is available with negative domain of frequency ?




Thank you in advance.



Answer



Even though I think there is a lot of valuable general information in Stanley Pawlukiewicz's answer and in Royi's answer, I think that some specific questions have not been answered, at least as far as I understand the OP's questions.


Let me go through the 3 bullet points in the OP one by one:




  1. If you mean how the error function depends on the filter coefficients, then for a length N FIR filter you simply have H(ejω)=N1n=0h[n]ejnω=cH(ω)h


where h is the vector of filter coefficients, c(ω) is given by c(ω)=[1,ejω,,ej(N1)ω], and H denotes the Hermitian conjugate. Clearly, (1) is a linear function of the filter coefficients, hence the error function E(ω) is linear in h.




  1. The sign of the error function is irrelevant, because you end up minimizing a squared error measure, which depends on |E(ω)|2, and which is, consequently, independent of the sign of E(ω).




  2. I did my best to understand what is meant by the third question but I failed. Maybe the OP can elaborate in a comment or by editing the question.





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