Blind Estimation Using Higher-Order Statistics

SNR Estimation for Multilevel Constellations Using Higher-Order Moments

In the signal-processing research community, a great deal of progress in higher-order statistics HOS began in the mids.

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These last fifteen years have witnessed a large number of theoretical developments as well as real applications. Blind Estimation Using Higher-Order Statistics focuses on the blind estimation area and records some of the major developments in this field. The book provides the reader with an introduction to HOS and goes on to illustrate its use in blind signal equalisation which has many applications including mobile communications , blind system identification, and blind sources separation a generic problem in signal processing with many applications including radar, sonar and communications.

There is also a chapter devoted to robust cumulant estimation, an important problem where HOS results have been encouraging.

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Blind Estimation Using Higher-Order Statistics is an invaluable reference for researchers, professionals and graduate students working in signal processing and related areas. Read more Read less.

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Jitendra K Tugnait

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Don't have a Kindle? Springer; Softcover reprint of hardcover 1st ed.

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Vehicular Technology , vol. Tugnait, "Doubly-selective fading channel equalization: Tugnait, "On doubly selective channel estimation using superimposed training and discrete prolate spheroidal sequences," IEEE Trans. Signal Processing , Vol. He, "Iterative joint channel estimation and data detection using superimposed training: He, "Doubly-selective channel estimation using data-dependent superimposed training and exponential basis models," IEEE Trans.

Tugnait and Xiaohong Meng, "On superimposed training for channel estimation: Liang, Tongtong Li and J.

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He, "Iterative joint channel estimation and data detection using superimposed training: Offer period 4th Sep to 30th Sep. Tugnait, "Improved parameter estimation with noisy data for linear models using higher order statistics and inverse filter criteria," IEEE Signal Processing Letters , vol. Here's how terms and conditions apply Go Cashless: Recommended articles Citing articles 0. Tugnait, "Identification of multivariable stochastic linear systems via spectral analysis given time-domain data," IEEE Trans. Typically it is assumed that the noise is white and the signal-to-noise ratio is known.

Tongtong Li, Zhi Ding, J. Soonho Jeong and J. Tongtong Li and J.

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Tugnait, "A bit-map-assisted dynamic queue protocol for multi-access wireless networks with multiple packet reception," IEEE Trans. Jinghong Ma and J. Tugnait, "Identification of closed Loop linear systems via cyclic spectral analysis given noisy input-output time-domain data," IEEE Trans.

Automatic Control , vol. Huang, "Multistep linear predictors-based blind identification and equalization of multiple-input multiple-output channels," IEEE Trans. Yi Zhou and J.