Proceedings of 1994 28th Asilomar Conference on Signals, Systems and Computers (1994)
Pacific Grove, CA, USA
Oct. 31, 1994 to Nov. 2, 1994
A. Delopoulos , Comput. Sci. Div., Athens Nat. Tech. Univ., Greece
S. Kollias , Comput. Sci. Div., Athens Nat. Tech. Univ., Greece
Conventional design techniques for analysis and synthesis filters in subband processing applications guarantee perfect reconstruction of the original signal from its subband components. The resulting filters lose, however, their optimality when additive noise, due for example, to signal quantization, disturbs the subband sequences. In this paper, we propose filter design techniques that minimize the reconstruction mean squared error taking into account the second order statistics of signals and noise in the case of either stochastic or deterministic signals. A novel recursive, pseudo-adaptive algorithm is proposed for efficient design of these filters. Analysis and derivations are extended to two dimensional signals and filters using powerful Kronecker product notation. A prototype application of the proposed ideas in subband coding is presented. Simulations illustrate the superior performance of the proposed filter banks versus conventional perfect reconstruction filters.<
noise, signal reconstruction, encoding, band-pass filters, quantisation (signal), higher order statistics, stochastic processes, adaptive filters, adaptive signal processing, two-dimensional digital filters
A. Delopoulos and S. Kollias, "Optimal filterbanks for signal reconstruction from noisy subband components," Proceedings of 1994 28th Asilomar Conference on Signals, Systems and Computers(ACSSC), Pacific Grove, CA, USA, 1995, pp. 991-995.