Title :
Reduced parameter Volterra filters
Author :
Nowak, Robert D. ; Van Veen, Barry D.
Author_Institution :
Dept. of Electr. & Comput. Eng., Wisconsin Univ., Madison, WI, USA
Abstract :
To reduce the number of parameters in the Volterra filter a tensor product basis approximation is considered. The approximation can be implemented much more efficiently than the original Volterra filter. In addition, because the design methods are based on partial characterization of the Volterra filter, the approximations are also useful in reducing the complexity of identification and modelling problems. Useful bounds are obtained on the approximation error
Keywords :
Volterra equations; approximation theory; error analysis; filtering theory; parameter estimation; tensors; approximation error; design methods; identification problems; modelling problems; reduced parameter Volterra filters; tensor product basis approximation; Approximation error; Design methodology; Kernel; Linear approximation; Nonlinear filters; Random variables; Tensile stress; USA Councils; Vectors;
Conference_Titel :
Acoustics, Speech, and Signal Processing, 1995. ICASSP-95., 1995 International Conference on
Conference_Location :
Detroit, MI
Print_ISBN :
0-7803-2431-5
DOI :
10.1109/ICASSP.1995.479862
