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The frequency of a sinusoidal signal is a well defined quantity. However, often in practice, signals are not truly sinusoidal, or even aggregates of sinusoidal components. Nonstationary signals in particular do not lend themselves well to decomposition into sinusoidal components. For such signals, the notion of frequency loses its effectiveness, and one(More)
This paper, which addresses the important issue of estimating the instantaneous frequency (IF) of a signal, is a sequel to the paper which appears in this issue, and dealt with the concepts relating to the IF. In this paper the concept of IF is extended to be able to cope with discrete time signals. The specific problem explored is that of estimating the IF(More)
— This paper deals with the problem of blind separation of nonstationary sources in the underdetermined case, i.e. more sources than sensors, using time–frequency distributions (TFDs). We propose a new algorithm to achieve the separation based on a main assumption of time–frequency (TF) disjoint sources that allows an explicit exploitation of(More)
The Wigner-Ville distribution (WVD) is a valuable tool for time-frequency signal analysis. In order to implement the WVD in real time, an efficient algorithm and architecture have been developed which may be implemented with-commercial components. This algorithm successively computes the analytic signal corresponding to the input signal, forms a weighted(More)
This paper presents a method for estimating the instantaneous frequency (IF) of multicomponent signals. The technique involves, firstly, the transformation of the one-dimensional signal to the two-dimensional time–frequency (TF) domain using a reduced interference quadratic TF distribution. IF estimation of signal components is then achieved by implementing(More)
A new algorithm for extracting features from images for object recognition is described. The algorithm uses higher order spectra to provide desirable invariance properties, to provide noise immunity, and to incorporate nonlinearity into the feature extraction procedure thereby allowing the use of simple classifiers. An image can be reduced to a set of 1D(More)
—This paper presents the essential elements for developing objective methods of assessment of the performance of time-frequency signal analysis techniques. We define a measure for assessing the resolution performance of time-frequency distributions (TFDs) in separating closely spaced components in the time-frequency domain. The measure takes into account(More)
This paper presents two new time-frequency distributions (TFDs) based on kernels with compact support (KCS) namely the separable (CB) (SCB) and the polynomial CB (PCB) TFDs. The implementation of this family of TFDs follows the method developed for the Cheriet-Belouchrani (CB) TFD. The mathematical properties of these three TFDs are analyzed and their(More)