Time-recursive architectures and wavelet transform
Emmanuel N. Frantzeskakis, John S. Baras, K.J.R. Liu · IEEE International Conference on Acoustics Speech and Signal Processing · 1993
The time-recursive computation has been proved as a particularly useful tool in real-time data compression and in transform domain adaptive filtering, with applications in the areas of audio, radio, sonar, and video. An architectural framework for parallel time-recursive computation is proposed. The authors consider a class of linear operators that consists of the discrete time, time invariant, compactly supported, but otherwise arbitrary kernel functions. They define a shift property of the linear operators and reveal its relation with the time-recursive implementation. The potential of the proposed framework is demonstrated by designing a time-recursive architecture for the discrete wavelet transform.>