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A constraint optimization of low‐delay and low‐operation driven FIR digital filters for big data signal processing
Author(s) -
Hirakawa Tomohiro,
Nakamoto Masayoshi
Publication year - 2018
Publication title -
electronics and communications in japan
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.131
H-Index - 13
eISSN - 1942-9541
pISSN - 1942-9533
DOI - 10.1002/ecj.12089
Subject(s) - finite impulse response , digital filter , signal processing , reduction (mathematics) , optimization problem , computer science , constraint (computer aided design) , digital signal processing , linear filter , filter design , algorithm , mathematical optimization , filter (signal processing) , mathematics , computer hardware , geometry , computer vision
In big data signal processing system, low‐delay and low‐operation driven digital filters are required for large amounts of data processing. We introduce a design method for low‐delay FIR (finite impulse response) filters with semi‐sparse coefficients. The semi‐sparse coefficients stand for to have some 0 ± 1 values with real values. The semi‐sparse coefficients lead to reduction of number of multipliers. We show the design problem of the filters are formulated in a constraint optimization problem. Also, we propose a design algorithm to solve the design problem. Using the filters, the number of multipliers can be reduced. Finally, we present examples to demonstrate the effectiveness of the proposed method.