IEEE Circuits and Systems Magazine - Q4 2021 - 1

Circuits
and Systems
IEEE
MAGAZINE
Volume 21, Number 4
Fourth Quarter 2021
Features
4 Analysis, Prediction, and Control
of Epidemics: A Survey from Scalar
to Dynamic Network Models
Lorenzo Zino and Ming Cao
During the ongoing COVID-19 pandemic, mathematical models of epidemic spreading
have emerged as powerful tools to produce valuable predictions of the evolution of the
pandemic, helping public health authorities decide which intervention policies should
be implemented. The study of these models-grounded in the systems theory and often
analyzed using control-theoretic tools-is an extremely important research area for many
researchers from different fields, including epidemiology, engineering, physics, mathematics,
computer science, sociology, economics, and management. In this survey, we review
the history and present the state of the art in the modeling, analysis, and control of epidemic
dynamics. We discuss different approaches to epidemic modeling, either deterministic
or stochastic, ranging from the first implementations of scalar systems of differential
equations to describing the epidemic spreading at the population level, and to more recent
models on dynamic networks, which capture the spatial spread and the time-varying
nature of human interactions.
24 Precision Adaptive MFCC Based on
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R2SDF-FFT and Approximate Computing for
Low-Power Speech Keywords Recognition
Bo Liu, Xiaoling Ding, Hao Cai, Wentao Zhu, Zhen Wang,
Weiqiang Liu, and Jun Yang
IEEE Circuits and Systems Magazine (ISSN 1531-636X)
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This paper presents system-architecture-circuits co-designs for computing the MFCC
feature extraction for speech keywords recognition. The trade-off between accuracy
and power consumption under various background noises is achieved by using the
8-stage radix-2 single-path delay feedback FFT (R2SDF-FFT) and the precision selfadaptive
architecture with approximate computing. The R2SDF-FFT structure with the
fine-grained bit-width quantization can reduce 35.7% of memory size. Approximate
multiplication and addition with Dual-Vdd are proposed to further improve the FFT
computing energy efficiency. Finally, we present the precision self-adaptive MFCC
architecture with the proposed FFT, which can be dynamically configured to use
two calculation modes with different hardware settings according to the input speech
background noise. Implemented and evaluated under 22 nm technology, the power consumption
of the proposed design can be reduced by up to 76.3%, while the accuracy
increased by 0.8%.
Digital Object Identifier 10.1109/MCAS.2021.3056252
FOURTH QUARTER 2021
IEEE CIRCUITS AND SYSTEMS MAGAZINE
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IEEE Circuits and Systems Magazine - Q4 2021

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