Title :
Eigenstructure approach for characterization of FIR PR filterbanks with order one polyphase
Author :
Murhuvel, A. ; Makur, Anamitra
Author_Institution :
Dept. of Electr. Commun. Eng., Indian Inst. of Sci., Bangalore, India
fDate :
10/1/2001 12:00:00 AM
Abstract :
A new approach for the characterization of M-channel finite impulse response (FIR) perfect reconstruction (PR) filterbanks is proposed. By appropriately restricting the eigenstructure of the polyphase matrix of the bank, a complete characterization of order-one polyphase matrices is obtained in which the polynomial part is in a block diagonal form. Nilpotent matrices play a crucial role in the structure. This structure allows imposing restrictions on the order of the inverse of the polyphase matrix and/or analysis-synthesis delay (reconstruction delay). Next, we derive an alternate complete characterization in terms of the degree of the determinant and the McMillan degree of order-one polyphase matrix, which we call the dyadic-based characterization. The characterization of Vaidyanathan and Chen (1995) for matrices with anticausal inverse turns out to be a special case of the proposed characterization. The dyadic-based characterization is more suitable for design without any above-mentioned restriction since it allows better initialization. We finally present design examples with different cost functions
Keywords :
FIR filters; channel bank filters; delays; eigenvalues and eigenfunctions; matrix inversion; network synthesis; signal reconstruction; FIR PR filterbanks; McMillan degree; analysis-synthesis delay; anticausal inverse; cost functions; determinant degree; dyadic-based characterization; eigenstructure; eigenstructure approach; finite impulse response filterbanks; inverse polyphase matrix; nilpotent matrices; order one polyphase; order-one polyphase matrices; perfect reconstruction filterbanks; polyphase matrix; reconstruction delay; Cost function; Delay; Design optimization; Finite impulse response filter; Helium; Linear matrix inequalities; Nonlinear filters; Phase modulation; Polynomials;
Journal_Title :
Signal Processing, IEEE Transactions on