A Neuromorphic Electrothermal Processor for Near-Sensor Computing

Vahideh Shirmohammadli

doi:10.1002/admt.202200361

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A Neuromorphic Electrothermal Processor for Near-Sensor Computing

2022-07-19

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Vahideh Shirmohammadli

Behraad Bahreyni *

DOI：10.1002/admt.202200361

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Abstract

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The statistical processing of sensor data using conventional digital computers is inefficient in terms of time, energy usage, and communication bandwidth, among others. Therefore, new approaches are sought to create context and make sense of the sensor data using special-purpose computers that excel in specific computation tasks. Herein, the requirements for physical systems to perform sophisticated nonlinear computations needed for real-time pattern recognition in data, specifically sensor data, are discussed. The focus is on physical reservoir computing as a neuromorphic computing approach. Considering energy flow as the coupling mechanism between nonlinear dynamic systems, it is demonstrated that many physical systems satisfy the basic requirements for building reservoir computers. Using physical reservoir computers brings up exciting opportunities for near- or in-sensor computing as to how new data are collected and processed. The concepts are demonstrated through a novel physical computation platform, where off-the-shelf, temperature-sensitive resistors are used to perform various standard and specific computational tasks. This platform is used as a near-sensor processor to detect particular events. How a similar platform may be used for in-sensor neuromorphic computations is further discussed.

Keywords:

near-sensor computing

neuromorphic computing

reservoir computing

thermistors