Results 131 to 140 of about 3,059,110 (191)
A Novel Time-Frequency Similarity Method for P-Wave First-Motion Polarity Detection. [PDF]
Sensors (Basel)Yao Y, Xu X, Wang J, Liu L, Ma Z.
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Neural responses to perceptual and sexual ambiguity in facial images: an ERP and time-frequency analysis. [PDF]
Sci RepSano T, Kawabata H.
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Automating time × frequency annotations of delphinid whistles by adapting a foundational transformer neural network. [PDF]
Sci RepZhang X, Liu X, Alksne MN, Roch MA.
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Separating feedforward and feedback dynamics using time-frequency resolved connectivity: A hybrid model of left ventral occipitotemporal cortex in word reading. [PDF]
Imaging Neurosci (Camb)You J, Hauk O, Salmelin R, van Vliet M.
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Journal of Econometric Methods, 2020
Abstract Wavelet analysis is widely used to trace macroeconomic and financial phenomena in time–frequency domains. However, existing wavelet measures diverge from conventional regression estimators. Furthermore, a direct comparison between wavelet and traditional regression analyses is difficult.
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Abstract Wavelet analysis is widely used to trace macroeconomic and financial phenomena in time–frequency domains. However, existing wavelet measures diverge from conventional regression estimators. Furthermore, a direct comparison between wavelet and traditional regression analyses is difficult.
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Time-frequency projection filters and time-frequency signal expansions
IEEE Transactions on Signal Processing, 1994We consider the problems of designing a linear, time-varying filter with a specified "time-frequency (TF) pass region" and of constructing an orthonormal basis for the parsimonious expansion of signals located in a given TF support region. These problems of TF filtering and TF signal expansion are reduced to the problem of designing a "TF subspace", i ...
F. Hlawatsch, W. Kozek
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2003
Conventionally, time series have been studied either in the time domain or the frequency domain. The representation of a signal in the time domain is localized in time, i.e. the value of the signal at each instant in time is well defined. However, the time representation of a signal is poorly localized in frequency, i.e.
A. Ramachandra Rao +2 more
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Conventionally, time series have been studied either in the time domain or the frequency domain. The representation of a signal in the time domain is localized in time, i.e. the value of the signal at each instant in time is well defined. However, the time representation of a signal is poorly localized in frequency, i.e.
A. Ramachandra Rao +2 more
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IEEE Signal Processing Letters, 1999
A new method for the estimation of the signal subspace and noise subspace based on time-frequency signal representations is introduced. The proposed approach consists of the joint block-diagonalization (JBD) of a set of spatial time-frequency distribution matrices.
Belouchrani, Adel., Amin, Moeness G.
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A new method for the estimation of the signal subspace and noise subspace based on time-frequency signal representations is introduced. The proposed approach consists of the joint block-diagonalization (JBD) of a set of spatial time-frequency distribution matrices.
Belouchrani, Adel., Amin, Moeness G.
openaire +1 more source