Linear Phase FIR Filter Design for Digital Hearing Aids Using a Neural Network-Based Optimization

Simple item page
dc.contributor.authorChivapreecha, Sorawat
dc.contributor.authorYospanya, Poonna
dc.date.accessioned2026-08-06T10:45:24Z
dc.date.available2026-08-06T10:45:24Z
dc.date.issued2024-01-01
dc.description.abstractA neural network-based optimization for the design of linear phase digital filters used in digital hearing aid applications is presented in this paper. To achieve hearing loss compensation, a 53-tap finite impulse response (FIR) filter is utilized, and the weights of the trained network can be used to obtain the impulse response of the FIR filter. The target frequency response or label comes from the audiogram, the training data is created, and a linear perceptron supervised learning model is used. Audiogram matchings are shown in design examples. The proposed neural network-based design approach can give a very high accuracy, high processing speed when compared with the existing methods, and also low complexity in filter structure realization.
dc.identifier.citationIEEE Region 10 Annual International Conference Proceedings TENCON, 465-468, 2024
dc.identifier.doi10.1109/TENCON61640.2024.10903076
dc.identifier.issn21593442
dc.identifier.other2-s2.0-105000386784
dc.identifier.urihttps://dspace.kmitl.ac.th/handle/123456789/15453
dc.sourceIEEE Region 10 Annual International Conference Proceedings TENCON
dc.subjectdigital hearing aid
dc.subjectFIR filter
dc.subjectlinear perceptron
dc.subjectlinear phase
dc.subjectneural network
dc.subjectsupervised learning
dc.titleLinear Phase FIR Filter Design for Digital Hearing Aids Using a Neural Network-Based Optimization
dc.typeConference Paper

Files

Collections

Research