A constraint optimization of low‐delay and low‐operation driven FIR digital filters for big data signal processing

Abstract

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. K E Y W O R D Sbig data signal processing, FIR digital filters, low delay, low operation Electron Comm Jpn. 2018;101:43-51.