Open AccessLOW POWER DIGITAL FILTERING USING ADAPTIVE APPROXIMATE PROCESSING: FIR FILTER STRUCTURES
Author(s) -
Jeffrey Ludwig
Publication year - 2021
Language(s) - English
DOI - 10.37516/global.j.elec.comp.eng.2021.0140
Subject(s) - half band filter , adaptive filter , filter design , digital filter , computer science , root raised cosine filter , voltage controlled filter , low pass filter , filter (signal processing) , prototype filter , electronic engineering , band stop filter , kernel adaptive filter , cascaded integrator–comb filter , high pass filter , digital signal processing , algorithm , computer hardware , engineering , computer vision
Techniques for reducing power consumption in digital circuits have become increasingly important because of the growing demand for portable multimedia devices. Digital filters, being ubiquitous in such devices, are a prime candidate for low power design. Algorithmic approaches to low power frequency-selective digital filtering which are based on the concepts of adaptive approximate processing have been developed and formalized by introducing the class of approximate filtering algorithms in which the order of a digital filter is dynamically varied to provide time-varying stopband attenuation in proportion to the time-varying signal-to-noise ratio (SNR) of the input signal, while maintaining a fixed SNR at the filter output. Since power consumption in digital filter implementations is proportional to the order of the filter, dynamically varying the filter order is a strategy which may be used to conserve power. In this paper we introduce a class of approximate filter structures using FIR digital filter constituent elements. These filter structures are explored and shown to be an important element in the characterization of approximate filtering algorithms.