A Constraint Optimization of Low-delay and Low-operation Driven FIR Digital Filters for Big Data Signal Processing
Tomohiro Hirakawa, Masayoshi Nakamoto · IEEJ Transactions on Electronics Information and Systems · 2018
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 ± values with real values. The semi-sparse coefficients leads 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.