Comparison of binomial, ZAM and minimum cross-entropy time-frequency distributions of intracardiac heart sounds

Bulgrin, James R.; Rubal, Bernard J.; Posch, T.E.; Moody, Joe M.

doi:10.1109/acssc.1994.471481

Cited by 4 publications

(1 citation statement)

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“…In engineering, where the distributions are called time-frequency distributions, the main aim has been to understand time-varying spectra [14,15,16,17,18,19]. Among the many areas to which they have been applied are heart sounds, heart rate, the electroencephalogram (EEG), the electromyogram (EMG) [20,21,22,23,24], machine fault monitoring [11,17,18,19,25,26], radar and sonar signals, acoustic scattering [14,16,27], speech processing [28,29], analysis of marine mammal sounds [30,31], musical instruments [32], linear and nonlinear dynamical systems [33,34,35], among many others. Our aim is the following.…”

Section: C(t ω) For the Signal X(t)mentioning

confidence: 99%

Nonlinear Transformation of Differential Equations into Phase Space

Cohen

Galleani

2004

EURASIP J. Adv. Signal Process.

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Time-frequency representations transform a one-dimensional function into a two-dimensional function in the phase-space of time and frequency. The transformation to accomplish is a nonlinear transformation and there are an infinite number of such transformations. We obtain the governing differential equation for any two-dimensional bilinear phase-space function for the case when the governing equation for the time function is an ordinary differential equation with constant coefficients. This connects the dynamical features of the problem directly to the phase-space function and it has a number of advantages

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