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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.


Papers
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Proceedings ArticleDOI
01 Nov 2019
TL;DR: This paper deals with extraction of statistical features from obtained 2-Dimensional data using STFT and performed classification in high frequency band for epilepsy and proposed Random Forest (RF) classifier achieved accuracy of 90%.
Abstract: The EEG signal consist various frequency bands, which represents human activities like emotion, attention sleep stage etc. For the detection of epileptical seizures, it is required to perform classification on the basis of various EEG segments. This paper, presents performance analysis of gamma band in EEG signal using short-time fourier transform (STFT). It also gives comparison of various classification methods and achieves very good accuracy with some classification techniques. Analysis has been performed with following stages like STFT, extraction of gamma frequency band, statistical features extraction and finally applied to classifier. This paper deals with extraction of statistical features from obtained 2-Dimensional data using STFT and performed classification in high frequency band for epilepsy. Here, proposed Random Forest (RF) classifier achieved accuracy of 90%.

31 citations

Journal ArticleDOI
TL;DR: The design problem of a Fourier-based filtering scheme in rotated time-frequency domains is revisited and a formulation that does not require knowledge of the statistics of the corrupting noise is derived.
Abstract: The concept of rotation in the joint time-frequency plane can be exploited in order to generalize classical Fourier-based operations. It is known that filtering in rotated time-frequency domains can lead to significant performance advantages for certain types of signals as compared to conventional linear time invariant systems. In this correspondence, we revisit the design problem of such a scheme and derive a formulation that does not require knowledge of the statistics of the corrupting noise. Simulations have been used to confirm the validity of the proposed solution.

31 citations

Journal ArticleDOI
TL;DR: This paper describes one such approach, based upon ordinary least squares deconvolution of induced responses to input functions encoding the onset of different components within each trial, and considers optimal forms for convolution models ofinduced responses, in terms of impulse response basis function sets.

31 citations

Proceedings ArticleDOI
01 Oct 2007
TL;DR: In this paper, a study of the permanent magnet synchronous motor (PMSM) running under demagnetization has been carried out by means of two dimensional finite element analysis (FEA), and simulations results were compared with experimental results.
Abstract: This paper presents a study of the permanent magnet synchronous motor (PMSM) running under demagnetization. The simulation has been carried out by means of two dimensional (2-D) finite element analysis (FEA), and simulations results were compared with experimental results. The demagnetization fault is analyzed by means of decomposition of stator currents obtained at different speeds. The Hilbert Huang transform (HHT) is used as processing tool. This transformation represents time-dependent series in a two-dimensional (2-D) time-frequency domain by extracting instantaneous frequency components within the signal through an Empirical Mode Decomposition (EMD) process.

31 citations

Proceedings ArticleDOI
21 Oct 2001
TL;DR: The main benefits of the proposed reassignment stage are that it yields an improved time-frequency localisation estimate relative to standard methods, and that it produces a measure of the variance of these estimates to be used as an aid in later processing.
Abstract: The reassignment method for the short-time Fourier transform is proposed as a technique for improving the time and frequency estimates of musical audio data. Based on this representation, four classes of expected objects (sinusoid, unresolved sinusoid, transient and noise) are proposed and explained. Pattern classification methods are then used to extract objects conforming to these classes from individual frames of the reassigned spectrogram, with each frame being examined independently. Results for several simple real-world examples are presented, showing the capability of this method even without the aid of tracking from frame to frame. The main benefits of the proposed reassignment stage are that it yields an improved time-frequency localisation estimate relative to standard methods, and that it produces a measure of the variance of these estimates to be used as an aid in later processing.

31 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
2023164
2022338
2021253
2020229
2019261
2018320