The Experts below are selected from a list of 16539 Experts worldwide ranked by ideXlab platform
B Boashash - One of the best experts on this subject based on the ideXlab platform.
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a new discrete time Analytic Signal for reducing aliasing in discrete time frequency distributions
European Signal Processing Conference, 2007Co-Authors: John M Otoole, M Mesbah, B BoashashAbstract:The commonly used discrete-time Analytic Signal for discrete time-frequency distributions (DTFDs) contains spectral energy at negative frequencies which results in aliasing in the DTFD. A new discrete-time Analytic Signal is proposed that approximately halves this spectral energy at the appropriate discrete negative frequencies. An empirical comparison shows that aliasing is reduced in the DTFD using the proposed Analytic Signal rather than the conventional Analytic Signal. The time domain characteristics of the two Analytic Signals are compared using an impulse Signal as an example, where the DTFD of the conventional Signal produces more artefacts than the DTFD of the proposed Analytic Signal. Furthermore, the proposed discrete Signal satisfies two important properties, namely the real part of the Analytic Signal is equal to the original real Signal and the real and imaginary parts are orthogonal.
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Signal enhancement by time frequency peak filtering
IEEE Transactions on Signal Processing, 2004Co-Authors: B Boashash, M MesbahAbstract:Time-frequency peak filtering (TFPF) allows the reconstruction of Signals from observations corrupted by additive noise by encoding the noisy Signal as the instantaneous frequency (IF) of a frequency modulated (FM) Analytic Signal. IF estimation is then performed on the Analytic Signal using the peak of a time-frequency distribution (TFD) to recover the filtered Signal. This method is biased when the peak of the Wigner-Ville distribution (WVD) is used to estimate the encoded Signal's instantaneous frequency. We characterize a class of Signals for which the method implemented using the pseudo WVD is approximately unbiased. This class contains deterministic bandlimited nonstationary multicomponent Signals in additive white Gaussian noise (WGN). We then derive the pseudo WVD window length that gives a reduced bias when TFPF is used for Signals from this class. Testing of the method on both synthetic and real life newborn electroencephalogram (EEG) Signals shows clean recovery of the Signals in noise level down to a Signal-to-noise ratio (SNR) of -9 dB.
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estimating and interpreting the instantaneous frequency of a Signal i fundamentals
Proceedings of the IEEE, 1992Co-Authors: B BoashashAbstract:The concept of instantaneous frequency (IF), its definitions, and the correspondence between the various mathematical models formulated for representation of IF are discussed. The extent to which the IF corresponds to the intuitive expectation of reality is also considered. A historical review of the successive attempts to define the IF is presented. The relationships between the IF and the group-delay, Analytic Signal, and bandwidth-time (BT) product are explored, as well as the relationship with time-frequency distributions. The notions of monocomponent and multicomponent Signals and instantaneous bandwidth are discussed. It is shown that these notions are well described in the context of the theory presented. >
Pushpendra Singh - One of the best experts on this subject based on the ideXlab platform.
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novel fourier quadrature transforms and Analytic Signal representations for nonlinear and non stationary time series analysis
Royal Society Open Science, 2018Co-Authors: Pushpendra SinghAbstract:The Hilbert transform (HT) and associated Gabor Analytic Signal (GAS) representation are well known and widely used mathematical formulations for modelling and analysis of Signals in various applic...
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novel fourier quadrature transforms and Analytic Signal representations for nonlinear and non stationary time series analysis
arXiv: Signal Processing, 2018Co-Authors: Pushpendra SinghAbstract:The Hilbert transform (HT) and associated Gabor Analytic Signal (GAS) representation are well-known and widely used mathematical formulations for modeling and analysis of Signals in various applications. In this study, like the HT, to obtain quadrature component of a Signal, we propose the novel discrete Fourier cosine quadrature transforms (FCQTs) and discrete Fourier sine quadrature transforms (FSQTs), designated as Fourier quadrature transforms (FQTs). Using these FQTs, we propose sixteen Fourier-Singh Analytic Signal (FSAS) representations with following properties: (1) real part of eight FSAS representations is the original Signal and imaginary part is the FCQT of the real part, (2) imaginary part of eight FSAS representations is the original Signal and real part is the FSQT of the real part, (3) like the GAS, Fourier spectrum of the all FSAS representations has only positive frequencies, however unlike the GAS, the real and imaginary parts of the proposed FSAS representations are not orthogonal to each other. The Fourier decomposition method (FDM) is an adaptive data analysis approach to decompose a Signal into a set of small number of Fourier intrinsic band functions which are AM-FM components. This study also proposes a new formulation of the FDM using the discrete cosine transform (DCT) with the GAS and FSAS representations, and demonstrate its efficacy for improved time-frequency-energy representation and analysis of nonlinear and non-stationary time series.
M Mesbah - One of the best experts on this subject based on the ideXlab platform.
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a new discrete time Analytic Signal for reducing aliasing in discrete time frequency distributions
European Signal Processing Conference, 2007Co-Authors: John M Otoole, M Mesbah, B BoashashAbstract:The commonly used discrete-time Analytic Signal for discrete time-frequency distributions (DTFDs) contains spectral energy at negative frequencies which results in aliasing in the DTFD. A new discrete-time Analytic Signal is proposed that approximately halves this spectral energy at the appropriate discrete negative frequencies. An empirical comparison shows that aliasing is reduced in the DTFD using the proposed Analytic Signal rather than the conventional Analytic Signal. The time domain characteristics of the two Analytic Signals are compared using an impulse Signal as an example, where the DTFD of the conventional Signal produces more artefacts than the DTFD of the proposed Analytic Signal. Furthermore, the proposed discrete Signal satisfies two important properties, namely the real part of the Analytic Signal is equal to the original real Signal and the real and imaginary parts are orthogonal.
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Signal enhancement by time frequency peak filtering
IEEE Transactions on Signal Processing, 2004Co-Authors: B Boashash, M MesbahAbstract:Time-frequency peak filtering (TFPF) allows the reconstruction of Signals from observations corrupted by additive noise by encoding the noisy Signal as the instantaneous frequency (IF) of a frequency modulated (FM) Analytic Signal. IF estimation is then performed on the Analytic Signal using the peak of a time-frequency distribution (TFD) to recover the filtered Signal. This method is biased when the peak of the Wigner-Ville distribution (WVD) is used to estimate the encoded Signal's instantaneous frequency. We characterize a class of Signals for which the method implemented using the pseudo WVD is approximately unbiased. This class contains deterministic bandlimited nonstationary multicomponent Signals in additive white Gaussian noise (WGN). We then derive the pseudo WVD window length that gives a reduced bias when TFPF is used for Signals from this class. Testing of the method on both synthetic and real life newborn electroencephalogram (EEG) Signals shows clean recovery of the Signals in noise level down to a Signal-to-noise ratio (SNR) of -9 dB.
Djamel Sayad - One of the best experts on this subject based on the ideXlab platform.
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Induction machine bearing fault diagnosis based on the axial vibration Analytic Signal
International Journal of Hydrogen Energy, 2016Co-Authors: Ammar Medoued, Mourad Mordjaoui, Youcef Soufi, Djamel SayadAbstract:Abstract This paper deals with a new induction motor defects diagnosis using the Axial Vibration Analytical Signal (AVAS). The Signal is generated by a bearing-defected induction machine. The calculation method may be divided into two main parts; the former is the Hilbert transform that consists in the first part normalization of the axial vibration and its comparison with the AVAS module. The second part consists in the extraction of feature vectors using the Signal Class Dependent Time Frequency Representation ( T F R S C D ) based on the Fisher contrast design of the non parametrically kernel. The Particle Swarm Optimization (PSO) is used to optimize the feature vectors size. The vibration severity caused by the bearing fault is investigated for different loads. This last decreases with the increasing level of the load. The obtained results are experimentally validated on a 5500 W induction motor test bench.
Mingsheng Liu - One of the best experts on this subject based on the ideXlab platform.
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envelope detection using generalized Analytic Signal in 2d qlct domains
Multidimensional Systems and Signal Processing, 2017Co-Authors: Kit Ian Kou, Mingsheng Liu, J Morais, Cuiming ZouAbstract:The hypercomplex 2D Analytic Signal has been proposed by several authors with applications in color image processing. The Analytic Signal enables to extract local features from images. It has the fundamental property of splitting the identity, meaning that it separates qualitative and quantitative information of an image in form of the local phase and the local amplitude. The extension of Analytic Signal of linear canonical transform domain from 1D to 2D, covering also intrinsic 2D structures, has been proposed. We use this improved concept on envelope detector. The quaternion Fourier transform plays a vital role in the representation of multidimensional Signals. The quaternion linear canonical transform (QLCT) is a well-known generalization of the quaternion Fourier transform. Some valuable properties of the two-sided QLCT are studied. Different approaches to the 2D quaternion Hilbert transforms are proposed that allow the calculation of the associated Analytic Signals, which can suppress the negative frequency components in the QLCT domains. As an application, examples of envelope detection demonstrate the effectiveness of our approach.
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Quaternion Wigner-Ville distribution associated with the linear canonical transforms
Signal Processing, 2017Co-Authors: Kit Ian Kou, Mingsheng Liu, Xiang-li FanAbstract:The quaternion linear canonical transform (QLCT), a generalization of the classical 2D Fourier transform, has gained much popularity in recent years because of its applications in many areas, including color image and Signal processing. There are relationship between Wigner distribution and ambiguity function. But, these relations are only suitable for complex-valued Signals, and have not been investigated in quaternion linear canonical transforms. The purpose of this paper is to propose an equivalent relationship for the quaternion Wigner distribution and quaternion ambiguity function in the QLCT setting. First, we propose the 2D quaternion Wigner distribution (QLWD) and quaternion ambiguity function associated with the QLCT. Next, the relationship between these two novel concepts are derived. Moreover, the connection with the corresponding Analytic Signal are investigated. Examples with bandpass Analytic Signal illustrate the features of the proposed distributions. Finally a novel algorithm for the detection of quaternion-valued linear frequency-modulated Signal is presented by using the proposed QLWD. HighlightsThe QLCT, a generalization of the classical 2D Fourier transform, has applications in color image and Signal processing.This paper presents new notions for the quaternion Wigner distribution (QLWD) and the corresponding ambiguity function in the QLCT setting.Connection with the corresponding Analytic Signal are investigated.Examples with bandpass Analytic Signal illustrate the features of the proposed distributions.A novel algorithm for the detection of quaternion-valued linear frequency-modulated Signal is presented by the proposed QLWD.
