Abstract
The use of time frequency distributions (TFDs) with adaptive kernels for the spectral estimation of non stationary signals has been shown to be an extremely useful tool in many applications. Nevertheless, their high computational cost, due to the necessity to calculate a new kernel in each time instance, poses an important problem in real time applications. Given that many real signals show intervals of relative stationarity, in this work we propose an algorithm for the control of the instant of adaptation in this type of technique, based on the detection of situations of quasi-stationarity of the signal. By way of the analysis of real and artificial signals, and applying our algorithm to a specific TFD, we clearly show the advantages of this new technique.
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© 1997 Springer-Verlag Berlin Heidelberg
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Vila, J.A., Presedo, J., Fernandez Delgado, M., Iglesias, R., Barro, S. (1997). Improvement in the computational efficiency in the analysis of signals by way of adaptive time frequency distributions. In: Pichler, F., Moreno-Díaz, R. (eds) Computer Aided Systems Theory — EUROCAST'97. EUROCAST 1997. Lecture Notes in Computer Science, vol 1333. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0025071
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DOI: https://doi.org/10.1007/BFb0025071
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