Kit Wing Chan

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Based on the linear prediction property of sinusoidal signals, two constrained weighted least squares frequency estimators for multiple real sinusoids embedded in white noise are proposed. In order to achieve accurate frequency estimation, the first algorithm uses a generalized unit-norm constraint, while the second method employs a monic constraint. The(More)
Based on the linear prediction (LP) property of sinusoidal signals, a closed-form unbiased frequency estimator for a real sinusoid in white noise is proposed. The frequency estimator, which is derived by minimizing a constrained least squares cost function, can be considered as a reformulation of the well known Pisarenko harmonic decomposer (PHD). Online(More)
Based on the equation-error approach, a weighted least squares algorithm with a generalized unit-norm constraint is developed for unbiased infinite impulse response (HR) system identification in the presence of white input and/or output noise. Through using a weighting matrix, the proposed estimator can be considered as a generalization of the(More)
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