Digital filter design
The design of arbitrary FIR digital filters using the eigenfiltermethod
IEEE Transactions on Signal Processing
Multiband least squares FIR filter design
IEEE Transactions on Signal Processing
Complex coefficient nonrecursive digital filter design using aleast-squares method
IEEE Transactions on Signal Processing
Thoughts on least squared-error optimal windows
IEEE Transactions on Signal Processing
Design and characterization of optimal FIR filters with arbitraryphase
IEEE Transactions on Signal Processing
Peak-constrained least-squares optimization
IEEE Transactions on Signal Processing
IEEE Transactions on Signal Processing
Iterative reweighted least-squares design of FIR filters
IEEE Transactions on Signal Processing
Constrained least square design of FIR filters without specifiedtransition bands
IEEE Transactions on Signal Processing
Weighted least-squares design and characterization of complex FIRfilters
IEEE Transactions on Signal Processing
Least squared error FIR filter design with transition bands
IEEE Transactions on Signal Processing
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In FIR filter design problems, filter specifications do not constrain in any way the ideal frequency response inside the transition regions. Most existing L"2-based filter design techniques utilize this flexibility in order to improve their performance. In this paper we propose a new general method for the weighted L"2-based design of arbitrary FIR filters. In particular, we propose a well-defined optimization criterion that depends on the selection of the desired response inside the transition regions. By optimizing our criterion we obtain desired responses that produce weighted mean square error optimum filters with extremely good characteristics. The proposed method is computationally simple since it requires the solution of a linear system of equations.