Title :
A multi-layer 2D adaptive filtering architecture based on McClellan transformation
Author :
Liu, K.J.R. ; Wu, An-Yeu Andy
Author_Institution :
Electr. Eng. Dept., Maryland Univ., College Park, MD, USA
Abstract :
A fully pipelined systolic array structure for multidimensional adaptive filtering is proposed. It utilizes the McClellan transformation (MT) to reduce the total number of parameters used in the 2D filter. A new multilayer triangular array, which is based on QR-decomposition recursive least squares (RLS) (QRD-RLS) as well as the projection method, are derived for the ´1-D prototype filter´ of MT. The hardware complexity for the new architecture is only O(N). The system latency is also reduced from O(N) to O(log2N). The QRD-RLS algorithm is suitable for real-time image processing such as video signal processing.
Keywords :
adaptive filters; least squares approximations; pipeline processing; recursive filters; systolic arrays; two-dimensional digital filters; video signal processing; McClellan transformation; QR-decomposition recursive least squares; hardware complexity; multi-layer 2D adaptive filtering; multidimensional adaptive filtering; pipelined systolic array structure; projection method; real-time image processing; system latency; triangular array; video signal processing; Adaptive filters; Delay; Hardware; Least squares methods; Multidimensional systems; Nonhomogeneous media; Prototypes; Resonance light scattering; Signal processing algorithms; Systolic arrays;
Conference_Titel :
Circuits and Systems, 1993., ISCAS '93, 1993 IEEE International Symposium on
Conference_Location :
Chicago, IL
Print_ISBN :
0-7803-1281-3
DOI :
10.1109/ISCAS.1993.394145
