Topic
Time–frequency analysis
About: Time–frequency analysis is a research topic. Over the lifetime, 5407 publications have been published within this topic receiving 104346 citations.
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TL;DR: A whale optimization algorithm (WOA)-optimized orthogonal matching pursuit (OMP) with a combined time–frequency atom dictionary with comparisons with the state of the art in the field are illustrated in detail, which highlight the advantages of the proposed method.
91 citations
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TL;DR: A novel time–frequency method for the measurement of oxygen saturation using the photoplethysmogram (PPG) signals from a standard pulse oximeter machine to derive a 3D Lissajous figure is presented.
Abstract: We present a novel time–frequency method for the measurement of oxygen saturation using the photoplethysmogram (PPG) signals from a standard pulse oximeter machine. The method utilizes the time–frequency transformation of the red and infrared PPGs to derive a 3D Lissajous figure. By selecting the optimal Lissajous, the method provides an inherently robust basis for the determination of oxygen saturation as regions of the time–frequency plane where high- and low-frequency signal artefacts are to be found are automatically avoided.
89 citations
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TL;DR: In this paper, the authors proposed a new and powerful method capable of detecting minor incipient faults in power transformers based on dyadic-orthonormal wavelet transform analysis, which decomposes a given faulty neutral current response into other signals which represent a smoothed and detailed version of the original.
Abstract: Detection of major faults in power transformers during impulse tests has never been an issue, but is rather difficult when only a minor fault, say a sparkover between adjacent coils or turns and lasting for a few microseconds, occurs. However, detection of such a type of fault is very important to avoid any catastrophic situation. In this paper, the authors propose a new and powerful method capable of detecting minor incipient faults. The approach is based on wavelet transform analysis, particularly the dyadic-orthonormal wavelet transform. The key idea underlying the approach is to decompose a given faulty neutral current response into other signals which represent a smoothed and detailed version of the original. The decomposition is performed by the multiresolution signal decomposition technique. Preliminary simulation work demonstrated here shows that the proposed method is robust and far superior to other existing methods to resolve such types of faults.
89 citations
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TL;DR: It has been shown that the wavelet transform is a flexible time-frequency decomposition tool that can form the basis of useful signal analysis, and coding schemes.
Abstract: The wavelet transform has a powerful time-frequency analysis and signal-coding tool suitable for use in the manipulation of complex nonstationary signals. This article provides an overview of the emerging role of wavelet-transform analysis in biomedical signal processing and analysis. It also provides a brief overview of the theory of the transform in its two distinct and very different forms: continuous and discrete. In conclusion, it has been shown that the wavelet transform is a flexible time-frequency decomposition tool that can form the basis of useful signal analysis, and coding schemes. It is envisaged that the future will see further application of the wavelet transform to biomedical signal analysis, as the emerging technologies based on them are honed for practical purposes.
89 citations
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TL;DR: The earlier known phenomena, connected with voluntary movements, were confirmed and a new evidence concerning focal ERD/surround ERS and beta activity post-movement synchronization was found.
89 citations