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A State-Space Approach for Adaptive Notch Digital Filters with Unbiased Parameter-Estimation | IEEE Conference Publication | IEEE Xplore

A State-Space Approach for Adaptive Notch Digital Filters with Unbiased Parameter-Estimation


Abstract:

A state-space approach for adaptive second-order IIR notch digital filters is investigated. First, a simplified iterative algorithm is derived from a gradient descent met...Show More

Abstract:

A state-space approach for adaptive second-order IIR notch digital filters is investigated. First, a simplified iterative algorithm is derived from a gradient descent method to minimize the mean-squared output of an adaptive notch digital filter. Second, the stability and frequency-estimation bias are analyzed by employing a first-order linear dynamical system. As a result, it is clarified that the resulting parameter estimate is unbiased. Finally, a numerical example is presented to demonstrate the validity and effectiveness of the proposed adaptive state-space notch digital filters and the frequency-estimation bias analysis.
Date of Conference: 25-28 June 2023
Date Added to IEEE Xplore: 15 August 2023
ISBN Information:
Conference Location: Jeju, Korea, Republic of

I. Introduction

Adaptive notch filtering is well known as a useful technique for detecting, removing, enhancing and retrieving sinusoidal signals of unknown frequency from additive broad-band noise. It is widely applied in digital communications, control, radar, sonar, biomedical engineering, active noise control, and so on [1]–[3]. Adaptive notch digital filters can mainly be classified into two classes of filters such as the direct-form filters with constrained poles and zeros [4]–[10] or the lattice-based filters [11]–[14]. The former usually possesses biased frequency estimate [6], [8], [10], whereas the latter yields unbiased frequency estimate for a single sinusoid [11], [12]. It is noted that a simplified iterative algorithm was used in [11], [14], an ordinary differential equation approach was employed in [12], and the affine combination of Regalia's simplified lattice algorithm and lattice gradient algorithm was utilized in [13].

References

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