Abstract
The extraction of a signal from noisy data is a common problem in many fields of science and engineering. There are many approaches that have been employed. A particularly challenging problem can be extracting broadband signals from broadband noise, especially when the noise and signal span common frequencies. However, if the local spectral properties of the signal and noise are different, then a phase space approach to filtering can be effective for separating the signal from the noise. In this chapter, we present the basic idea behind this method of filtering, which involves the design of time-varying filters based on the phase space properties of the signal or noise. The approach is demonstrated by application to marine mammal sounds to remove background ocean noise.
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Acknowledgements
It is a pleasure to dedicate this chapter to David Middleton. The author’s research was supported by a grant from the Office of Naval Research (N00014-06-1-0009).
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Loughlin, P.J. (2012). Denoising and Time-Frequency Analysis of Signals. In: Cohen, L., Poor, H., Scully, M. (eds) Classical, Semi-classical and Quantum Noise. Springer, New York, NY. https://doi.org/10.1007/978-1-4419-6624-7_10
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DOI: https://doi.org/10.1007/978-1-4419-6624-7_10
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