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A class of nonparametric detectors for dependent input data

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2 Author(s)

A class of nonparametric detectors is formulated for dependent input sequences of sampled data. Detectors in this class are nonadaptive modifications of standard nonparametric detectors designed for independent inputs and operate on multivariate samples derived by grouping the dependent univariate input samples. These groups are transformed to single variables and processed according to the corresponding standard nonparametric detection scheme. Performance analysis is initially based on assumptions implying independence of the multivariate samples, and results are then shown to remain valid under weaker conditions. Two modified one-channel detectors are analyzed to illustrate the improved performance achieved over corresponding standard non-parametric detectors.

Published in:

Information Theory, IEEE Transactions on  (Volume:21 ,  Issue: 4 )

Date of Publication:

Jul 1975

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