Masking of Time-Frequency Patterns in Applications of Passive Underwater Target Detection
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- @Article{Sildam:2010:eurasipJASP,
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title = "Masking of Time-Frequency Patterns in Applications of
Passive Underwater Target Detection",
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author = "Juri Sildam",
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year = "2010",
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journal = "EURASIP Journal on Advances in Signal Processing",
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volume = "2010",
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pages = "Article ID 298038",
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keywords = "genetic algorithms, genetic programming",
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ISSN = "16876172",
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oai = "oai:CiteSeerX.psu:10.1.1.396.4388",
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URL = "http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.396.4388",
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URL = "http://asp.eurasipjournals.com/content/pdf/1687-6180-2010-298038.pdf",
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DOI = "doi:10.1155/2010/298038",
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language = "eng",
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publisher = "Hindawi Publishing Corporation",
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size = "11 pages",
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abstract = "Spectrogram analysis of acoustical sounds for
underwater target classification is used when loud
nonstationary interference sources overlap with a
signal of interest in time but can be separated in
time-frequency (TF) domain. We propose a signal masking
method which in a TF plane combines local statistical
and morphological features of the signal of interest. A
dissimilarity measure D of adjacent TF cells is used
for local estimation of entropy H, followed by
estimation of {$\Delta$}H=Htc{$-$}Hfc entropy
difference, where Hfc is calculated along the time axis
at a mean frequency fc and Htc is calculated along the
frequency axis at a mean time tc of the TF window,
respectively. Due to a limited number of points used in
{$\Delta$}H estimation, the number of possible
{$\Delta$}H values, which define a primary mask, is
also limited. A secondary mask is defined using
morphological operators applied to, for example, H and
{$\Delta$}H. We demonstrate how primary and secondary
masks can be used for signal detection and
discrimination, respectively. We also show that the
proposed approach can be generalised within the
framework of Genetic Programming.",
- }
Genetic Programming entries for
Juri Sildam
Citations