Browsing by Author "Ouelha S."
Now showing items 1-7 of 7
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An improved time–frequency noise reduction method using a psycho-acoustic Mel model
Ouelha S.; Aïssa-El-Bey A.; Boashash B. ( Elsevier Inc. , 2018 , Article)This paper addresses the problem of noise reduction in non-stationary signals. The paper first describes a human physiology based time?frequency (TF) representation (HPTF) using Mel filterbanks. It is then used to improve ... -
Automatic signal abnormality detection using time-frequency features and machine learning: A newborn EEG seizure case study
Boashash B.; Ouelha S. ( Elsevier B.V. , 2016 , Article)Time-frequency (TF) based machine learning methodologies can improve the design of classification systems for non-stationary signals. Using selected TF distributions (TFDs), TF feature extraction is performed on multi-channel ... -
Designing high-resolution time–frequency and time–scale distributions for the analysis and classification of non-stationary signals: a tutorial review with a comparison of features performance
Boashash B.; Ouelha S. ( Elsevier Inc. , 2018 , Article)This paper deals with the problem of extracting information from non-stationary signals in the form of features that can be used for effective decision-making in both data analysis and machine learning for automatic ... -
Refining the ambiguity domain characteristics of non-stationary signals for improved time–frequency analysis: Test case of multidirectional and multicomponent piecewise LFM and HFM signals
Boashash, Boualem; Jawad, Brahim K.; Ouelha, Samir ( Elsevier Inc. , 2018 , Article)This paper aims at providing a more accurate description of the ambiguity domain characteristics of a piecewise multicomponent non-stationary signals with focus on piece-wise linear frequency modulated (LFM) (PW-LFM) signal ... -
Time-frequency diagnosis, condition monitoring, and fault detection
Powers, E.J.; Shin, Y.-J.; Mack Grady, W.; Böhme, J.F.; Carstens-Behrens, S.; Papandreou-Suppappola, A.; Hlawatsch, F.; Boudreaux-Bartels, G.F.; Beghdadi, A.; Iordache, R.; Boashash, B.; Djebbari, A.; Ouelha, S.; Onchis, D.M.... more authors ... less authors ( Elsevier Inc. , 2016 , Book chapter)This chapter aims to further illustrate the (t,f) approach by selecting a few key generic applications of diagnosis and monitoring. The topic is represented by seven sections. One key application is electrical power ... -
Time-frequency methods in radar, sonar, and acoustics
Marple, S.L., Jr.; Barbarossa, S.; Ferguson, B.G.; Lo, K.W.; Frazer, G.J.; Boashash, B.; Chandran, V.; Gholami, A.; Ouelha, S.... more authors ... less authors ( Elsevier Inc. , 2016 , Book chapter)The fields of radar and sonar are traditionally key application areas and testing grounds for advances in signal processing, including time-frequency (t,f) methodologies; their significance is demonstrated in seven ... -
Time-frequency synthesis and filtering
Hlawatsch, F.; Matz, G.; Boashash, B.; Ouelha, S.; Stanković, S.; Hassanpour, H.... more authors ... less authors ( Elsevier Inc. , 2016 , Book chapter)This chapter presents methods and techniques to design time-varying linear systems such as filters with precise time-frequency (t,f) specifications; this capability can then allow one to model and predict accurately the ...