Titlebook: Blind Estimation Using Higher-Order Statistics; Asoke Kumar Nandi (David Jardine Chair of Electric Book 1999 Springer Science+Business Med

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Book 1999communications). There is also a chapter devoted to robust cumulantestimation, an important problem where HOS results have beenencouraging. ..Blind Estimation Using Higher-Order Statistics. is an invaluablereference for researchers, professionals and graduate students workingin signal processing and

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sonar andcommunications). There is also a chapter devoted to robust cumulantestimation, an important problem where HOS results have beenencouraging. ..Blind Estimation Using Higher-Order Statistics. is an invaluablereference for researchers, professionals and graduate students workingin signal processing and978-1-4419-5078-9978-1-4757-2985-6

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Asoke Kumar Nandi (David Jardine Chair of Electric

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https://doi.org/10.1007/3-540-29252-7ignals of an array of microphones, as long as the signals to be extracted fulfil certain conditions [62, 63] . Wireless communications is another usual application field of signal separation techniques. In a CDMA (Code Division Multiple Access) environment several users share the same radio channel

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Higher-Order and Cyclostationary Statistics,er statistical information. Autocorrelations and cross-correlations are examples of second-order statistics (SOS). The power spectrum which is widely used and contains useful information is again based on the second-order statistics in that the power spectrum is the one-dimensional Fourier transform

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Blind Signal Equalisation,his is in effect inverse system modelling, an architecture that is well-known in adaptive filtering theory. The cascade of channel and equaliser should constitute an identity operation, with the exception of a time delay and linear phase shift being allowed.

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Blind Source Separation,om another set of measurements which were generated as mixtures of the initial set. Since usually neither the original signals — called . — nor the mixing transformation are known, this is certainly a challenging problem of multichannel blind estimation. One of the most typical examples is the socal