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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.


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Journal ArticleDOI
TL;DR: Preliminary results strongly support the vision of seeking the right form of sparsity for the right application to enable sparsity-cognizant estimation of robust parametric models for nonstationary signal analysis, through readily appreciated applications in frequency-hopping communications and speech compression.
Abstract: Recent research and experimental findings, as well as technological development and commercialization efforts, suggest that even a modest amount of data can deliver superior signal modeling and reconstruction performance if sparsity is present and accounted for. Early sparsity-aware signal processing techniques have mostly targeted stationary signal analysis using offline algorithms for signal and image reconstruction from Fourier samples. On the other hand, sparsity-aware time-frequency tools for nonstationary signal analysis have recently received growing attention. In this context, sparse regression has offered a new paradigm for instantaneous frequency estimation, over classical time-frequency representations. Standard techniques for estimating model parameters from time series yield erroneous fits when, e.g., abrupt changes or outliers cause model mismatches. Accordingly, the need arises for basic research in robust processing of nonstationary parametric models that leverage sparsity to accomplish tasks such as tracking of signal variations, outlier rejection, robust parameter estimation, and change detection. This article aims at delineating the analytical background of sparsity-aware time-series analysis and introducing sparsity-aware robust and nonstationary parametric models to the signal processing readership, through readily appreciated applications in frequency-hopping (FH) communications and speech compression. Preliminary results strongly support the vision of seeking the right form of sparsity for the right application to enable sparsity-cognizant estimation of robust parametric models for nonstationary signal analysis.

31 citations

Proceedings ArticleDOI
28 Dec 2015
TL;DR: In this article, the authors reconstruct the phase of modified spectrograms of audio signals from the analysis of mixtures of sinusoids and obtain relationships between phases of successive time frames in the Time-Frequency domain.
Abstract: This paper introduces a novel technique for reconstructing the phase of modified spectrograms of audio signals. From the analysis of mixtures of sinusoids we obtain relationships between phases of successive time frames in the Time-Frequency (TF) domain. To obtain similar relationships over frequencies, in particular within onset frames, we study an impulse model. Instantaneous frequencies and attack times are estimated locally to encompass the class of non-stationary signals such as vibratos. These techniques ensure both the vertical coherence of partials (over frequencies) and the horizontal coherence (over time). The method is tested on a variety of data and demonstrates better performance than traditional consistency-based approaches. We also introduce an audio restoration framework and observe that our technique outperforms traditional methods.

31 citations

Journal ArticleDOI
TL;DR: This paper proposes a processing method of marine-mammal signals, well adapted to a real passive underwater context, and tries to overcome the two major limitations of the warping operator principle.
Abstract: Processing marine-mammal signals for passive oceanic acoustic tomography or species classification and monitoring are problems that have recently attracted attention in scientific literature. For these purposes, it is necessary to use a method which could be able to extract the useful information about the processed data, knowing that the underwater environment is highly nonstationary. In this context, time-frequency (TF) or time-scale methods constitute a potential approach. Practically, it has been observed that the majority of TF structures of the marine-mammal signals are highly nonlinear. This fact affects dramatically the performances achieved by the Cohen's class methods, these methods being efficient in the presence of linear TF structures. Fortunately, thanks to the warping operator principle, it is possible to generate other class of time-frequency representations (TFRs). The new TFRs may analyze nonlinear chirp signals better than Cohen's class does. In spite of its mathematical elegance, this principle is limited in real applications by two major elements. First, as we will see, its implementation leads to a considerable growth of the signal length. Consequently, from operational point of view, this principle is limited to short synthetic signals. Second, the design of a single warping operator can be inappropriate if the analyzed signal is multicomponent. Furthermore, the choice of "adapted" warping operator becomes a problem when the signal components have different TF behaviors. In this paper, we propose a processing method of marine-mammal signals, well adapted to a real passive underwater context. The method tries to overcome the two aforementioned limitations. Also, the first step consists in data size reducing by the detection of the TF regions of interests (ROIs). Furthermore, in each ROI, a technique which combines some typical warping operators is used. The result is an analytical characterization of the instantaneous frequency laws (IFLs) of signal components. The simulations on real underwater data show the performances of this method in comparison with classical ones

31 citations

Journal ArticleDOI
TL;DR: A novel ISAR imaging algorithm for nonuniformly rotating targets in the low SNR environment based on the parameter estimation approach is presented and several numerical examples, analyses of the noise tolerance performance for the proposed approaches, andISAR imaging results demonstrate the superior performance of the proposed method.
Abstract: The inverse synthetic aperture radar (ISAR) imaging for nonuniformly rotating target has always been a challenging task due to the time-varying Doppler parameter, especially in the low signal-to-noise ratio (SNR) environment. In this paper, a novel ISAR imaging algorithm for nonuniformly rotating targets in the low SNR environment based on the parameter estimation approach is presented. First, the received signal in this work in a range bin is modeled as a multicomponent cubic phase signal (CPS) after motion compensation. Two approaches, namely coherently integrated modified cubic phase function (CIMCPF) and coherently integrated modified high-order ambiguous function (CIMHAF), are proposed to, respectively, estimate the second-order and the third-order coefficients in the CPS. Thanks to the coherent integrations developed in both CIMCPF and CIMHAF, they demonstrate excellent low SNR performance. Moreover, to efficiently implement the proposed approach, the nonuniform fast Fourier transform (NUFFT) is utilized in this work. Due to the usage of the NUFFT, the computational cost is reduced, and the search procedure also dispenses with the nonuniformly spaced signal. Finally, CIMCPF and CIMHAF are applied to produce ISAR image for a maneuvering target based on the CPS model. Several numerical examples, analyses of the noise tolerance performance for the proposed approaches, and ISAR imaging results demonstrate the superior performance of the proposed method.

31 citations

Journal ArticleDOI
TL;DR: A special purpose hardware system for time-frequency signal analysis based on the S-method which has the significant advantage of using the short time Fourier transform as an intermediate step in its implementation.
Abstract: A special purpose hardware system for time-frequency signal analysis is presented. This system is based on the S-method which has the significant advantage of using the short time Fourier transform as an intermediate step in its implementation. The hardware designed for a fixed point arithmetic is well-structured and suitable for VLSI implementation. An example including an error analysis is also provided.

31 citations


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