An Adaptive Acoustic Neuromorphic Auditory System
Martin Ziegler a b, Claudia Lenk a, Kalpan Ved a, Vishal Gubbi a, Kristina Nikiruy a, Tzvetan Ivanov a b, Steve Durstewitz a
a Micro- and Nanoelectronic Systems, Department of Electrical Engineering and Information Technology, TU Ilmenau, 98693, GERMANY
b Institute of Micro- and Nanotechnologies MacroNano®, TU Ilmenau, 98693, GERMANY
Proceedings of Neuronics Conference (Neuronics)
València, Spain, 2024 February 21st - 23rd
Organizers: Sabina Spiga and Juan Bisquert
Invited Speaker, Martin Ziegler, presentation 026
Publication date: 18th December 2023

Neuromorphic systems have experienced a rapid upswing in the last decade due to the increasing spread of machine learning systems, but also due to new technological possibilities through memristive devices that enable efficient hardware realizations of bio-inspired computing paradigms. In this talk, an auditory neuromorphic system will be presented that emulates the outstanding characteristics of the human sense of hearing. This includes a dynamic range of more than 120 dB sound pressure level (SPL), a frequency resolution of up to 0.1 %, an intensity discrimination of only 1 dB and adaptability at low sound levels in noisy environments. The neuromorphic system presented here emulates the properties of the sense of hearing by means of critical coupled oscillators. Therefore, a micro-electromechanical system- (MEMS) with feedback electronic is used to realize the sensory part, while networks based on memristive devices are used for subsequent information processing. Using this system as an example, important requirements for MEMS sensors and memristive devices will be discussed, and it will be shown how a new way of information processing beyond current approaches can open a new bio-inspired pathway toward the construction of cognitive electronics.

Funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) – Project - ID 434434223 – SFB 1461 and the Carl-Zeiss foundation  – Projects NeuroSensEar and MemWerk. 

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