Two algorithms for adaptive retrieval of slowly time-varyingmultiple cisoids in noise

Authors:
P. Tichavsky;P. Handel
Affiliations:
Inst. of Inf. Theory & Autom., Prague;-
Venue:
IEEE Transactions on Signal Processing
Year:
1995

Citing 0
Cited 8

A reduced-rank spectral approach to multi-sensor enhancement of large numbers of sinusoids in unknown noise fields

Signal Processing
Brief paper: Generalized adaptive notch filters with frequency debiasing for tracking of polynomial phase systems

Automatica (Journal of IFAC)
Self-optimizing generalized adaptive notch filters - comparison of three optimization strategies

Automatica (Journal of IFAC)
A new approach to active noise and vibration control-part II: the unknown frequency case

IEEE Transactions on Signal Processing
Generalized adaptive notch smoothing revisited

IEEE Transactions on Signal Processing
Estimation and tracking of complex-valued quasi-periodically varying systems

Automatica (Journal of IFAC)
Parallel frequency tracking with built-in performance evaluation

Digital Signal Processing
Generalized adaptive comb filters/smoothers and their application to the identification of quasi-periodically varying systems and signals

Automatica (Journal of IFAC)

Quantified Score

Hi-index	35.70

Visualization

Abstract

Two algorithms for tracking parameters of slowly varying multiple complex sine waves (cisoids) in noise (the multiple frequency tracker and the adaptive notch filter) are described. For high signal-to-noise ratio (SNR), the properties of the algorithms (i.e., stability, noise rejection, and tracking speed) are studied analytically using a linear filter approximation technique. The tradeoff between noise rejection and tracking error for both algorithms is shown to be similar. Different choices of the design variables are discussed, namely (i) minimal mean-square estimation error for random walk modeled frequency variations and (ii) minimal stationary estimation variance subject to a given tracking delay