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.
Papers published on a yearly basis
Papers
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TL;DR: In this paper, the authors evaluate the performance of the continuous wavelet transform and empirical mode decomposition in tandem with Hilbert transform in the analysis of a variety of classical nonlinear signals, underscoring a fundamental difference between the two approaches.
Abstract: Recently, there has been growing utilization of time-frequency transformations for the analysis and interpretation of nonlinear and nonstationary signals in a broad spectrum of science and engineering applications. The continuous wavelet transform and empirical mode decomposition in tandem with Hilbert transform have been commonly utilized in such applications, with varying success. This study evaluates the performance of the two approaches in the analysis of a variety of classical nonlinear signals, underscoring a fundamental difference between the two approaches: the instantaneous frequency derived from the Hilbert transform characterizes subcyclic and supercyclic nonlinearities simultaneously, while wavelet-based instantaneous frequency captures supercyclic nonlinearities with a comple- mentary measure of instantaneous bandwidth characterizing subcyclic nonlinearities. This study demonstrates that not only is the spectral content of the wavelet instantaneous bandwidth measure consistent with that of the Hilbert instantaneous frequency, but in the case of the Rossler system, produces identical oscillatory signature.
30 citations
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TL;DR: In this paper, a robust time-frequency approach based on pseudo-Wigner-Ville distribution assisted Renyi entropy (PWVD-RE) for vehicle detection is presented.
30 citations
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TL;DR: Two approaches to extract subsets from the time-frequency representation (TFR) for classification or recognition purposes are developed for TFRs obtained from the short time Fourier transform or the gliding minimum variance method.
30 citations
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07 Jun 1993
TL;DR: In this paper, a class of multilinear time-frequency signal representations was proposed for the detection and parameter estimation of signals characterized by a slowly varying complex envelope and a polynomial instantaneous phase.
Abstract: Proposes a class of multilinear time-frequency signal representations particularly useful for the detection and parameter estimation of signals characterized by a slowly varying complex envelope and a polynomial instantaneous phase. The main characteristics of the proposed representation is that it allows one to set up a sequential estimation procedure for estimating the coefficients of the signal instantaneous frequency. The performance of the method are given in terms of receiver operating characteristics and parameter estimation accuracy. >
30 citations
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18 Mar 2005TL;DR: The results obtained for real data prove the capability of the proposed approach for accurately detect and characterize signals with a complex TF behavior.
Abstract: The problem of signal detection, followed by a characterization stage, is considered in this paper. The main difficulties arising in the detection stage are caused by noise, which acts in a real environment, and by multiple time-frequency (TF) structures of the signal. In this paper a detection method based on the adaptive grouping of the TF information provided by a Gabor filter bank is proposed. A Viterbi-type algorithm is used as a tool for grouping of TF components. The results obtained for real data prove the capability of the proposed approach for accurately detect and characterize signals with a complex TF behavior.
30 citations