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AuthorO'Toole J.M.
AuthorBoashash B.
Available date2022-05-31T19:01:40Z
Publication Date2011
Publication NameEurasip Journal on Advances in Signal Processing
ResourceScopus
Identifierhttp://dx.doi.org/10.1155/2011/193797
URIhttp://hdl.handle.net/10576/31942
AbstractWe consider the problem of detecting an unknown signal from an unknown noise type. We restrict the signal type to a class of slowly varying periodic signals with harmonic components, a class which includes real signals such as the electroencephalogram or speech signals. This paper presents two methods designed to detect these signal types: the ambiguity filter and the time-frequency correlator. Both methods are based on different modifications of the time-frequency-matched filter and both methods attempt to overcome the problem of predefining the template set for the matched filter. The ambiguity filter method reduces the number of required templates by one half; the time-frequency correlator method does not require a predefined template set at all. To evaluate their detection performance, we test the methods using simulated and real data sets. Experiential results show that the two proposed methods, relative to the time-frequency-matched filter, can more accurately detect speech signals and other simulated signals in the presence of coloured Gaussian noise. Results also show that all time-frequency methods outperform the classical time-domain-matched filter for both simulated and real signals, thus demonstrating the utility of the time-frequency detection approach.
Languageen
SubjectDetection performance
Filter method
Gaussian noise
Harmonic components
Noise types
Performance evaluation
Periodic signal
Real data sets
Real signals
Simulated signals
Speech signals
Time domain
Time frequency
Time-frequency methods
Gaussian noise (electronic)
Matched filters
Signal detection
Speech communication
Time domain analysis
TitleTime-frequency detection of slowly varying periodic signals with harmonics: Methods and performance evaluation
TypeArticle
Volume Number2011
dc.accessType Abstract Only


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