Multi-component IF estimation

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Multi-component IF estimation

Show simple item record Hussain, Z.M. Boashash, B 2011-08-09T12:39:05Z 2011-08-09T12:39:05Z 2000-08
dc.identifier.citation Proceedings of the Tenth IEEE Workshop on Statistical Signal and Array Processing, 2000,Issue Date : 2000,On page(s): 559 en_US
dc.identifier.isbn 0-7803-5988-7
dc.description This paper presents an algorithm for estimating the IF and IB of a non-stationary multicomponent signal. (The most recent upgrade of the original software package that calculates Time-Frequency Distributions and Instantaneous Frequency estimators can be downloaded from the web site: This was the first software developed in the field, and it was first released publicly in 1987 at the 1st ISSPA conference held in Brisbane, Australia, and then continuously updated). A companion is the comprehensive book on Time-Frequency Signal Analysis and Processing available at: en_US
dc.description.abstract An adaptive approach to the estimation of the instantaneous frequency (IF) of non-stationary mono- and multi-component FM signals with additive Gaussian noise is presented. It is shown that the bias and variance of the IF estimate are functions of the lag window length. If there is a bias-variance trade-off, then the optimal window length for this tradeoff depends on the unknown IF law. Hence an adaptive algorithm with a time-varying and data-driven window length is needed. The adaptive algorithm can utilize any quadratic time-frequency distribution that satisfies certain conditions. A quadratic distribution that is most suitable for this approach is proposed. The algorithm estimates multiple IF laws by using a tracking algorithm for the signal components and utilizing the property that the proposed distribution enables non-parametric component amplitudes estimation. An extension of the proposed TFD consisting in the use of time-only kernels for adaptive IF estimation is also proposed. en_US
dc.language.iso en en_US
dc.publisher IEEE en_US
dc.subject Adaptive algorithm en_US
dc.subject Adaptive signal processing en_US
dc.subject Additive noise en_US
dc.subject Amplitude estimation en_US
dc.subject Frequency estimation en_US
dc.subject Gaussian noise en_US
dc.subject Separable Kernel en_US
dc.subject Signal processing algorithms en_US
dc.subject Signal resolution en_US
dc.subject Time frequency analysis en_US
dc.subject IF estimate bias en_US
dc.subject IF estimate variance en_US
dc.subject adaptive IF estimation en_US
dc.subject additive Gaussian noise en_US
dc.subject data-driven window length en_US
dc.subject instantaneous frequency estimation en_US
dc.subject lag window length en_US
dc.subject multi-component IF estimation en_US
dc.subject nonparametric component amplitude estimation en_US
dc.subject nonstationary mono-component FM signals en_US
dc.subject nonstationary multi-component FM signals en_US
dc.subject quadratic time-frequency distributions en_US
dc.subject time-only kernels en_US
dc.subject time-varying window length en_US
dc.subject tracking algorithm en_US
dc.title Multi-component IF estimation en_US
dc.type Article en_US

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