Now showing items 1-10 of 10

    • Characterising the Human Auditory System using a Linear Least-Squares System Identification Approach 

      DRENNAN, DENIS (Trinity College Dublin. School of Engineering. Discipline of Electronic & Elect. Engineering, 2019)
      Disabling hearing loss affects many millions of people around the world.Early identification and suitable interventions, e.g., the provision of hearing aids, cochlear implants, etc., can help but are limited ...
    • Deep Cross-Modal Alignment in Audio-Visual Speech Recognition 

      Sterpu, George (Trinity College Dublin. School of Engineering. Discipline of Electronic & Elect. Engineering, 2021)
      Modern studies in cognitive psychology have demonstrated that speech perception is a multimodal process, as opposed to a purely auditory one with visual carryover as in the classic view. This led researchers to investigate ...
    • Enabling Adaptable Future Networks: Trade-Offs and Resource Allocation Problems 

      SEXTON, CONOR (Trinity College Dublin. School of Engineering. Discipline of Electronic & Elect. Engineering, 2020)
      In this thesis, we illuminate the various trade-offs arising from the trend towards customisable networks, and propose resource allocation procedures to balance these trade-offs and facilitate the necessary coexistence of ...
    • The impact of visual speech on neural processing of auditory speech 

      O'Sullivan, Aisling (Trinity College Dublin. School of Engineering. Discipline of Electronic & Elect. Engineering, 2021)
      When we listen to someone speak, seeing their face can help us to understand them better, especially when there is background noise or other people speaking at the same time. Research examining the neural processes underlying ...
    • Massive MIMO technology for next generation of wireless networks 

      SABETI, PARNA (Trinity College Dublin. School of Engineering. Discipline of Electronic & Elect. Engineering, 2020)
      Large scale antenna or massive multiple input multiple output (MIMO) systems are one of the key enabling technologies for fifth generation (5G) of wireless communications networks and beyond. This technology offers huge ...
    • Molecular Organisation in “de Vries” Smectic Liquid Crystals: Characterisation and Theory 

      SWAMINATHAN, VIGNESHWARAN (Trinity College Dublin. School of Engineering. Discipline of Electronic & Elect. Engineering, 2018)
      The study of anomalous temperature dependence of smectic layer thickness began fifty years ago. Liquid crystals exhibiting such properties were later classified as de Vries smectic liquid crystals. In this thesis I have ...
    • On the Design and Analysis of Indoor Millimetre-Wave Cellular Networks under Human Body Blockage 

      Firyaguna, Fadhil (Trinity College Dublin. School of Engineering. Discipline of Electronic & Elect. Engineering, 2020)
      The wide spectrum available in the millimetre-wave band is key to provide enhanced capacity for the demands of the fifth-generation (5G) of cellular networks. However, the usage of millimetre-wave frequencies introduces a ...
    • On the Performance and Design Tradeoffs of Low Altitude UAV Small Cells in Urban Environments 

      GALKIN, BORIS (Trinity College Dublin. School of Engineering. Discipline of Electronic & Elect. Engineering, 2019)
      Cellular data demand continues to increase from year to year, and to manage this rising demand network operators adopt new technologies and designs for their cellular networks. Among these, network densification is seen ...
    • Sound Source Localization and Virtual Testing of Binaural Audio 

      O'Dwyer, Hugh (Trinity College Dublin. School of Engineering. Discipline of Electronic & Elect. Engineering, 2021)
      This thesis is concerned with aspects of our perception of spatial audio and with novel technology used to record, analyse and present it. The field of spatial audio has become increasingly prevalent with mediums such as ...
    • Taking advantage of correlated information for energy-aware scheduling in the IoT: A deep reinforcement learning approach 

      HRIBAR, JERNEJ (Trinity College Dublin. School of Engineering. Discipline of Electronic & Elect. Engineering, 2020)
      Millions of battery-powered sensors deployed for monitoring purposes in a multitude of scenarios, e.g., agriculture, smart cities, industry, etc., require energy-efficient solutions to prolong their lifetime. When these ...