STATISTICAL DESIGN OF RECURSIVE DIGITAL FILTERS USING ITERATIVE TECHNIQUES
IBRAHIM, F., HANAFY, A., GHONIEMY, S. (1985). STATISTICAL DESIGN OF RECURSIVE DIGITAL FILTERS USING ITERATIVE TECHNIQUES. EKB Journal Management System, 1(A.S.A.T. CONFERENCE 14-16 May 1985 r CAIRO), 1143-1160. doi: 10.21608/asat.1985.26583
F. IBRAHIM; A. HANAFY; S. GHONIEMY. "STATISTICAL DESIGN OF RECURSIVE DIGITAL FILTERS USING ITERATIVE TECHNIQUES". EKB Journal Management System, 1, A.S.A.T. CONFERENCE 14-16 May 1985 r CAIRO, 1985, 1143-1160. doi: 10.21608/asat.1985.26583
IBRAHIM, F., HANAFY, A., GHONIEMY, S. (1985). 'STATISTICAL DESIGN OF RECURSIVE DIGITAL FILTERS USING ITERATIVE TECHNIQUES', EKB Journal Management System, 1(A.S.A.T. CONFERENCE 14-16 May 1985 r CAIRO), pp. 1143-1160. doi: 10.21608/asat.1985.26583
IBRAHIM, F., HANAFY, A., GHONIEMY, S. STATISTICAL DESIGN OF RECURSIVE DIGITAL FILTERS USING ITERATIVE TECHNIQUES. EKB Journal Management System, 1985; 1(A.S.A.T. CONFERENCE 14-16 May 1985 r CAIRO): 1143-1160. doi: 10.21608/asat.1985.26583

STATISTICAL DESIGN OF RECURSIVE DIGITAL FILTERS USING ITERATIVE TECHNIQUES

International Conference on Aerospace Sciences and Aviation Technology
Article 91, Volume 1, A.S.A.T. CONFERENCE 14-16 May 1985 r CAIRO, May 1985, Page 1143-1160  XML PDF (2.58 MB)
Document Type: Original Article
DOI: 10.21608/asat.1985.26583
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Authors
F. IBRAHIM1; A. HANAFY2; S. GHONIEMY3
1MSC., Radar & Guidance Chairs, M.T.C., Cairo, Egypt.
2Ph.D.
3Ph.D., Radar & Guidance Chairs, M.T.C., Cairo, Egypt.
Abstract
In this paper, the linearization iterative method in frequency domain for the design of recursive digital filters having a desired spectral density characteristic is proposed. For getting the initial solution, the separat-ion of spectra algorithm is employed. This initial solution affects hardly the rate of convergence of the already existing (steepest descent) algori-thm. However a care has been made to the choice of the initial condition which has consequently lead to a better perfomrance than that obtained using nonoptimal initial solution for the same number of iterations. For the same near optimal initial solution the linearization algorithm has been applied. This algorithm has lead finally to a design procedure by which the filter parameters best approximate the desired specifications with smaller number of iterations. The extensive study of the practical results of the proposed and already existing algorithms has shown that, with the same initial solution the linearization results in a better performance with less computation time.
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