Title :
Armlets and balanced multiwavelets: flipping filter construction
Author_Institution :
Dept. of Math., Prairie View A&M Univ., TX, USA
fDate :
5/1/2005 12:00:00 AM
Abstract :
In the scalar-valued setting, it is well-known that the two-scale sequences {qk} of Daubechies orthogonal wavelets can be given explicitly by the two-scale sequences {pk} of their corresponding orthogonal scaling functions, such as qk=(-1)kp1-k. However, due to the noncommutativity of matrix multiplication, there is little such development in the multiwavelet literature to express the two-scale matrix sequence {Qk} of an orthogonal multiwavelet in terms of the two-scale matrix sequence {Pk} of its corresponding scaling function vector. This paper, in part, is devoted to this study for the setting of orthogonal multiwavelets of dimension r=2. In particular, the two lowpass filters are flipping filters, whereas the two highpass filters are linear phase. These results will be applied to constructing both a family of the most recently introduced notion of armlet of order n and a family of n-balanced orthogonal multiwavelets.
Keywords :
high-pass filters; low-pass filters; matrix algebra; wavelet transforms; Daubechies orthogonal wavelet; balanced multiwavelets flipping filter construction; highpass filter; lowpass filter; matrix multiplication; scaling function vector; two-scale matrix sequence; Digital filters; Finite impulse response filter; Mathematics; Multiresolution analysis; Nonlinear filters; Polynomials; Signal processing; Symmetric matrices; Vectors; Wavelet analysis; Armlet; balanced; multiwavelet; orthogonality; scaling function vector;
Journal_Title :
Signal Processing, IEEE Transactions on
DOI :
10.1109/TSP.2005.845468