Displaying similar documents to “On the uncertainty inequality as applied to discrete signals.”

Gravitational waves from coalescing binaries: a hierarchical signal detection strategy

S. Mohanty, S. Dhurandhar (1997)

Banach Center Publications

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The detection of gravitational waves from coalescing compact binaries would be a computationally intensive process if a single bank of template waveforms (i.e., a one step search) is used. We present, in this paper, an alternative method which is a hierarchical search strategy involving two template banks. We show that the computational power required by such a two step search, for an on-line detection of the one parameter family of Newtonian signals, is 1/8 of that required when an...

Classification in the Gabor time-frequency domain of non-stationary signals embedded in heavy noise with unknown statistical distribution

Ewa Świercz (2010)

International Journal of Applied Mathematics and Computer Science

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A new supervised classification algorithm of a heavily distorted pattern (shape) obtained from noisy observations of nonstationary signals is proposed in the paper. Based on the Gabor transform of 1-D non-stationary signals, 2-D shapes of signals are formulated and the classification formula is developed using the pattern matching idea, which is the simplest case of a pattern recognition task. In the pattern matching problem, where a set of known patterns creates predefined classes,...

Wavelet transform and binary coalescence detection

Jean-Michel Innocent, Bruno Torrésani (1997)

Banach Center Publications

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We give a short account of some time-frequency methods which are relevant in the context of gravity waves detection. We focus on the case of wavelet analysis which we believe is particularly appropriate. We show how wavelet transforms can lead to efficient algorithms for detection and parameter estimation of binary coalescence signals. In addition, we give in an appendix some of the ingredients needed for the construction of discrete wavelet decompositions and corresponding fast algorithms. ...