Abstract
This paper presents a new A-weighting filter’s design and explores the potential of using approximate multiplication for low-power digital A-weighting filter implementation. It presents a thorough analysis of the effects of approximate multiplication, coefficient quantization, the order of first-order sections in the filter’s cascade, and zero-pole pairings on the frequency response of the digital A-weighting filter. The proposed A-weighting filter was implemented as a sixth-order IIR filter using approximate odd radix-4 multipliers. The proposed filter was synthesized (Verilog to GDS) using the Nangate45 cell library, and MATLAB simulations were performed to verify the designed filter’s magnitude response and performance. Synthesis results indicate that the proposed design achieves nearly 70% reduction in energy (power-delay product) with a negligible deviation of the frequency response from the floating-point implementation. Experiments on acoustic noise suggest that the proposed digital A-weighting filter can be deployed in environmental noise measurement applications without any notable performance degradation.
Highlights
Noise pollution is a common problem in urban environments
In this paper we proposed an energy-efficient A-weighting infinite impulse response (IIR) digital filter that uses approximate multiplications and coefficient quantization
We have thoroughly assessed the impacts of quantization, pole-zero pairings, the positions of the first-order sections in the filter’s cascade, and the placement of AO-RAD4 approximate multipliers in the filter’s cascade on its performance
Summary
Noise pollution is a common problem in urban environments. Humans are continuously exposed to noise as they go about their daily lives. The effectiveness of approximate multipliers for achieving low-power processing motivated us to apply approximate multiplication inside the A-weighting filter. We show that we can ensure the minimal influence of approximate multiplication on the performance of the A-weighting filter and achieve power-efficient processing. This paper presents a new design for an approximate low-power digital A-weighting filter implemented as a sixth-order IIR filter with approximate multipliers. Synthesis results indicate that the proposed approximate IIR filter design achieves a nearly 70% reduction in energy (power-delay product) while preserving the required accuracy.
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