Basic Design of One-Dimensional Digital Filters

2020 ◽  
pp. 161-183
Author(s):  
Majid Ahmadi
Keyword(s):  
Digital Filters ◽  
Basic Design ◽  
One Dimensional

DESIGN OF 2-D DIGITAL FILTERS BASED ON THE OPTIMAL DECOMPOSITION OF MAGNITUDE SPECIFICATIONS

1993 ◽  
Vol 03 (03) ◽  
pp. 733-756 ◽  
Author(s):  
T.-B. DENG ◽  
M. KAWAMATA ◽  
T. HIGUCHI
Keyword(s):  
Singular Value Decomposition ◽  
Digital Filters ◽  
Matrix Decomposition ◽  
Decomposition Methods ◽  
Singular Value ◽  
The Other ◽  
Design Technique ◽  
One Dimensional ◽  
Rms Error ◽  
Value Decomposition

The optimal decomposition (OD) technique for decomposing 2-D magnitude specifications into 1-D ones is proposed. Differing from the conventional matrix decomposition methods such as the singular value decomposition (SVD), the OD of a 2-D magnitude specification matrix results in 1-D magnitude specifications which are always non-negative while the root mean-squared (rms) error in decomposition is minimum. Therefore, the OD is more suitable for designing 2-D digital filters (2DDFs) through designing one-dimensional digital filters (1DDFs) than the conventional matrix decomposition methods. Based on the OD, the problem of designing a recursive 2DDF can be reduced to one of designing a pair of 1DDFs, one 1-input/multi-output, and the other multi-input/ 1-output. Consequently, 2DDFs can easily be obtained by designing 1DDFs using the well-established 1-D design techniques. Three design examples are presented to illustrate that this OD-based 2DDF design technique is extremely efficient.

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