Multirate systems and filter banks
Multirate systems and filter banks
Atomic Decomposition by Basis Pursuit
SIAM Review
Psychoacoustics: Facts and Models
Psychoacoustics: Facts and Models
Overcomplete discrete wavelet transforms with rational dilation factors
IEEE Transactions on Signal Processing
IEEE Transactions on Signal Processing
Frequency-domain design of overcomplete rational-dilation wavelet transforms
IEEE Transactions on Signal Processing
Comparing measures of sparsity
IEEE Transactions on Information Theory
Design of linear-phase nonuniform filter banks with partial cosine modulation
IEEE Transactions on Signal Processing
Perfect reconstruction filter banks with rational sampling factors
IEEE Transactions on Signal Processing
IEEE Transactions on Signal Processing
IEEE Transactions on Signal Processing
A method for design of Mth-band filters
IEEE Transactions on Signal Processing
Rational sampling filter banks based on IIR filters
IEEE Transactions on Signal Processing
Iterated filter banks with rational rate changes connection withdiscrete wavelet transforms
IEEE Transactions on Signal Processing
Shear madness: new orthonormal bases and frames using chirpfunctions
IEEE Transactions on Signal Processing
A Nonlinear Method for Stochastic Spectrum Estimation in the Modeling of Musical Sounds
IEEE Transactions on Audio, Speech, and Language Processing
Wavelet Transform With Tunable Q-Factor
IEEE Transactions on Signal Processing
Sharper Symmetric Self-Hilbertian wavelets
Signal Processing
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This paper proposes an approach for designing a general two-band, FIR, critically sampled, rational rate filter bank (RFB) with perfect reconstruction (PR) and regularity properties. Designs obtained from this approach, when iterated, lead to rational discrete wavelet transforms (RADWTs) with adjustable dilation factor. The RFB design is based on solving a non-convex constrained optimization problem in which the non-linear constraints arise from the perfect reconstruction conditions. An iterative algorithm is used to solve the optimization problem through solving a simplified convex quadratic problem with linear constraints at each iteration step. Some examples are provided to demonstrate the use of bi-orthogonal RADWTs in applications such as signal separation which benefit from decompositions with suitably chosen dilation factors.