Thesis

Bio-inspired acoustic sensors and systems - from biology to engineering exploiting feedback computation

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Awarding institution
  • University of Strathclyde
Date of award
  • 2018
Thesis identifier
  • T15269
Person Identifier (Local)
  • 201573649
Qualification Level
Qualification Name
Department, School or Faculty
Abstract
  • In order to design sensors and systems that can be sensitive to small signal levels even when immersed by background noise, may require out-of-the-box thinking. Biology can provide inspiration to achieve that, allowing the engineering landscape to borrow interesting ideas with the aim to solve current human problems. Biological sensor, system and signal processing designs are a result of many million years of evolutionary processes, which make them very-power efficient and well-adapted to perform their functions in a living organism.;This thesis is an example of how acoustic engineering can look into biology in order to get inspiration to design novel ways for detecting, encoding and processing sound information. Sometimes the challenges behind innovation are on finding the proper tools to conceptualize and prototype novel ideas. Bio-inspired engineering offers a possible pathway for new technological advances using theoretical reasoning and appropriate physical modelling. Therefore, this body of work is a research study, which borrows ideas from biology and employs engineering techniques to prototype some new concepts of sensors, systems and signal processing.;Moreover, it suggests an unconventional methodology in acoustic engineering, aiming to demonstrate that novel acoustic sensor system concepts can perform peripheral signal processing at the transducer level such like some natural sensory systems do. Here, from the engineering perspective, the aim is to delay as much as possible the digitalization task while exploiting analogue mechanical-electrical-feedback based computations, therefore, a smart acoustic sensory system concept can be created targeting real-time signal processing applications.
Advisor / supervisor
  • Jackson, Joseph
  • Windmill, James
Resource Type
DOI
Date Created
  • 2018
Former identifier
  • 9912712592802996

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