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Automatic signal abnormality detection using time-frequency features and machine learning: A newborn EEG seizure case study
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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 ...
Time-frequency methods in radar, sonar, and acoustics
(
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 diagnosis, condition monitoring, and fault detection
(
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 synthesis and filtering
(
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 ...
Efficient software platform TFSAP 7.1 and Matlab package to compute Time?Frequency Distributions and related Time-Scale methods with extraction of signal characteristics
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Elsevier B.V.
, 2018 , Article)
This article describes the source code used in the TFSAP toolbox (Boashash, 2016). It is extended with additional functions to allow reproducible research as presented in Boashash and Ouelha (in press). These codes can be ...
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
(
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 ...
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
(
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 ...
An improved time–frequency noise reduction method using a psycho-acoustic Mel model
(
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 ...