LMS-based notch filter for the estimation of sinusoidal signals in noise

Xiao, Yegui; Tadokoro, Yoshiaki

doi:10.1016/0165-1684(95)00084-q

Cited by 43 publications

(30 citation statements)

References 15 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The larger the pole radius is, the narrower the bandwidth of the IIR notch filter. is the coefficient to be adjusted to fit the normalized frequency and its true value is calculated by (8) A simple adaptive algorithm to update the filter coefficient is the well-known PG parameterized by a positive step size parameter : (9) This gradient-based LMS-like algorithm is simple to be realized and is found to show good performance. Recently, Petraglia et al [12] have derived the stability bounds and steady-state coefficient variance for this algorithm, by using a gradient linearization technique [11].…”

Section: Filter Structure and A General Gradient Algorithmmentioning

confidence: 99%

“…There are many types of IIR notch filter structures developed in the literature [1]- [9]. Three typical ones are the IIR lattice notch filter [6], [7], the bilinear second-order IIR notch filter [4], [5], and the IIR notch filter with constrained poles and zeros [2].…”

Section: Introductionmentioning

confidence: 99%

“…APPENDIX A BRIEF DERIVATIONS OF NOISE VARIANCESNote that this IIR notch filter without the coefficient has the same form as the LMS-based notch filter,[9, Eq. (13)], with corresponding to .…”

mentioning

confidence: 99%

See 2 more Smart Citations

A new memoryless nonlinear gradient algorithm for a second-order adaptive IIR notch filter and its performance analysis

Xiao

Tadokoro

Kobayashi³

1998

IEEE Trans. Circuits Syst. II

View full text Add to dashboard Cite

Adaptive infinite inpulse-response (IIR) notch filters have been widely studied for many years. However, further efforts are still to be made to pursue new algorithms which work better than the conventional plain gradient algorithm but have little increase in complexity. In this paper, we employ the gradient linearization, Taylor series expansion, and calculus of variations to derive a novel memoryless nonlinear gradient algorithm for a second-order adaptive IIR notch filter, which improves the estimation performance considerably. Approximate closed-form expressions for the stability bounds on the step size parameter and the steady-state coefficient variance are also derived. Extensive simulations indicate the significant improvement that may be achieved using the new algorithm, and verify the validity of the analytical results.Index Terms-Frequency estimation, gradient algorithm, infinite impulse-response notch filtering, performance analysis.

show abstract

Section: Filter Structure and A General Gradient Algorithmmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

A new memoryless nonlinear gradient algorithm for a second-order adaptive IIR notch filter and its performance analysis

Xiao

Tadokoro

Kobayashi³

1998

IEEE Trans. Circuits Syst. II

View full text Add to dashboard Cite

show abstract

“…The LMS algorithm was applied in [2]- [4] to make the DFT adaptive and useful for non stationary signals. The same LMS algorithm was discussed and analyzed in [9] and [12] for real-valued signals with arbitrary frequencies. A set of gradient-based algorithms was proposed based on a p-power error criterion, and their statistical analysis was performed in 978-1-4799-0434-1/13/$31.00 ©20 13 IEEE detail in [13].…”

Section: Introductionmentioning

confidence: 98%

“…The above-mentioned gradient-based LMS and p-power algorithms are capable of providing reasonably good discrete Fourier coefficient (DFC) estimates and are quite efficient in terms of the number of multiplications required [2]- [4], [9], [12], [13]. However, their estimation and tracking performance may become inadequate for applications that fast convergence and low estimation error are simultaneously imposed.…”

Section: Introductionmentioning

confidence: 99%

Adaptive Fourier analysis using a variable step-size LMS algorithm

Xiao

Huang

Wei

2013

2013 9th International Conference on Information, Communications &Amp; Signal Processing

Self Cite

View full text Add to dashboard Cite

Adaptive Fourier analysis has numerous applica tions in biomedical engineering, music signal processing, digital communications, power engineering etc. So far, a lot of adaptive algorithms and systems have been developed and applied. In this paper, a variable step-size LMS (VSS-LMS) algorithm is proposed for adaptive Fourier analysis of noisy sinusoidal signals. It significantly outperforms the conventional LMS and p-power algorithms in both stationary and nonstationary environments at the expense of very little increase in computational cost. Extensive simulations as well as application to real noise signals generated by large-scale factory rotating machines are conducted to confirm the improved performance and tracking capabilities of the proposed algorithm.

show abstract

Research on switch compensation control for maglev flywheel battery

Gao

Cao

2018

IEEJ Transactions Elec Engng

View full text Add to dashboard Cite

In a maglev flywheel system, an unbalanced interference signal synchronous with the flywheel frequency will be produced because the flywheel rotor is uneven. This signal can reduce system control precision and stability, and make the system produce unbalance force vibration. Therefore, the signal should be filtered to reduce the effects on the control system. A vibration switching compensation control strategy is proposed based on the standard least mean squares (LMS) algorithm and one proportional–integral–derivative (PID) controller. The flywheel's rotational frequency is measured in real time as the switching reference, and different LMS algorithm step sizes and different PID controller parameters are adopted in different rotational frequencies. Simulation and experimental results verify the feasibility and effectiveness of the switch compensation strategy, which can reduce the control current amplitude and make the flywheel rotate around the inertial principal axis as much as possible. © 2018 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.

show abstract

LMS-based notch filter for the estimation of sinusoidal signals in noise

Cited by 43 publications

References 15 publications

A new memoryless nonlinear gradient algorithm for a second-order adaptive IIR notch filter and its performance analysis

A new memoryless nonlinear gradient algorithm for a second-order adaptive IIR notch filter and its performance analysis

Adaptive Fourier analysis using a variable step-size LMS algorithm

Research on switch compensation control for maglev flywheel battery

Contact Info

Product

Resources

About