A 2-D adaptive filter structure based on the McClellan transformation design technique for 2-D FIR filters is proposed as a means of achieving improved performance in 2-D adaptive filters. performance is compared to that of a direct form 2-D LMS structure in terms of learning characteristics and computational efficiency. It is first shown that if the transformation structure is constrained by a priori knowledge of contour shapes in the frequency domain, the 2-D adaptive algorithm results in greatly reduced computational requirements and more rapid learning characteristics, as compared to the direct form. The transformation filter is then generalized by including the contour parameters in the adaptive parameter set to eliminate the constraints on the frequency domain contours. Finally, it is shown how an orthogonal transformation can be incorporated to improve the convergence rate of the constrained transformation structure.
All Science Journal Classification (ASJC) codes
- Control and Systems Engineering
- Computer Science(all)
- Electrical and Electronic Engineering