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1

Mvuma, Aloys. "Adaptive IIR Filters for Single Interference Suppression in a BPSK DS CDMA System In Rayleigh Fading Channel." Tanzania Journal of Engineering and Technology 30, no. 1 (June 30, 2007): 65–73. http://dx.doi.org/10.52339/tjet.v30i1.398.

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In this paper, effect of a single narrow-band interference (NBI) on bit error rate (BER) performance for a binary phase shift keying (BPSK) synchronous direct-sequence code-division multiple access (DS CDMA) communication system operating in a frequency nonselective Rayleigh fading channel is analyzed. Second-order adaptive infinite impulseresponse (IIR) notch filters with plain gradient algorithm (GA) for suppression of NBI in the DS CDMA system are proposed. A general closed-form BER expression for the DS CDMA system with NBI suppression second order adaptive IIR notch filters is derived based on the standard Gaussian approximation (SGA) method. BER expressions are then derived for the allpass filter-based adaptive IIR notch filter and adaptive IIR notch filter with constrained poles and zeros, the two structures that are commonly found in literature. It is observed that both adaptive IIR notch filter structures exhibit comparable BER performance. Extensive computer simulation results are presented to verify the accuracy and limitations of the analysis.
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2

Yong Ching Lim, Yue Xian Zou, and N. Zheng. "A piloted adaptive notch filter." IEEE Transactions on Signal Processing 53, no. 4 (April 2005): 1310–23. http://dx.doi.org/10.1109/tsp.2005.843742.

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3

Regalia, Phillip A. "A Complex Adaptive Notch Filter." IEEE Signal Processing Letters 17, no. 11 (November 2010): 937–40. http://dx.doi.org/10.1109/lsp.2010.2075925.

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4

He, Yan Ping, and Hai Dong Zhang. "Simulation of Adaptive Filter Based on LMS Algorithm in Simulink." Advanced Materials Research 282-283 (July 2011): 299–302. http://dx.doi.org/10.4028/www.scientific.net/amr.282-283.299.

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The paper introduces the principle and structure of adaptive filter based on LMS algorithm, studies a design scheme of a single frequency adaptive notch filter, and simulates its working procedure by using the Simulink simulation tool. The simulation results show that the adaptive notch filter based on LMS algorithm has the better convergence and the smaller steady-state error than traditional notch filter in the appropriate parameter.
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5

Sukhumalchayaphong, S., and C. Benjangkaprasert. "Adaptive IIR Notch Filter with Modified Algorithm for Echo Cancellation." International Journal of Signal Processing Systems 5, no. 2 (June 2017): 75–78. http://dx.doi.org/10.18178/ijsps.5.2.75-78.

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6

Zhang, S., Dan Li, and J. Sun. "Power System Frequency Tracking Using an Adaptive Lattice Notch Filter." Key Engineering Materials 295-296 (October 2005): 673–80. http://dx.doi.org/10.4028/www.scientific.net/kem.295-296.673.

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A new approach for power system frequency estimation is proposed. The approach consists of two stage adaptive notch filters. The first stage eliminates harmonics and enhances the fundamental waveform. After the down-sampled processing, the second stage produces an accurate estimate of the fundamental frequency. The notch filter is based on all-pass filter with an efficient lattice structure and is simple to realize. Simulation is presented to demonstrate the effectiveness of the algorithm.
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7

YOKOE, Seiji, Yoshio IWATA, Hidenori SATO, and Toshihiko KOMATSUZAKI. "Vibration Control Using Adaptive Notch Filter." Proceedings of Conference of Hokuriku-Shinetsu Branch 2004.41 (2004): 181–82. http://dx.doi.org/10.1299/jsmehs.2004.41.181.

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8

Suzuki, Tatsuo, and Kazuyasu Hamada. "Adaptive Notch Filter with Global Stability." IFAC Proceedings Volumes 34, no. 14 (August 2001): 337–40. http://dx.doi.org/10.1016/s1474-6670(17)41644-2.

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9

Cheng, Mu-Huo, and Jau-Long Tsai. "A new IIR adaptive notch filter." Signal Processing 86, no. 7 (July 2006): 1648–55. http://dx.doi.org/10.1016/j.sigpro.2005.09.010.

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10

Joelianto, Endra. "On Minimal Second-order IIR Bandpass Filters with Constrained Poles and Zeros." Journal of Engineering and Technological Sciences 53, no. 4 (August 3, 2021): 210401. http://dx.doi.org/10.5614/j.eng.technol.sci.2021.53.4.1.

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In this paper, several forms of infinite impulse response (IIR) bandpass filters with constrained poles and zeros are presented and compared. The comparison includes the filter structure, the frequency ranges and a number of controlled parameters that affect computational efforts. Using the relationship between bandpass and notch filters, the two presented filters were originally developed for notch filters. This paper also proposes a second-order IIR bandpass filter structure that constrains poles and zeros and can be used as a minimal parameter adaptive digital second-order filter. The proposed filter has a wider frequency range and more flexibility in the range values of the adaptation parameters.
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11

Punchalard, Rachu. "Arctangent Gradient Based Adaptive Algorithm for a Second-Order Adaptive IIR Notch Filter." Applied Mechanics and Materials 781 (August 2015): 535–38. http://dx.doi.org/10.4028/www.scientific.net/amm.781.535.

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Frequency estimation based on adaptive notch filter is very attractive due to simplicity and economy. This paper presents an arctangent gradient (AG) based adaptive algorithm for a second-order constrained adaptive IIR notch filter (ANF). The motivation is to use an arctangent value of the gradient signal to adjust the filter parameter. It is revealed that for slow adaptation, the AG can be considered as an unbiased estimator. The quantitative simulations have been conducted to support the superior of the proposed AG algorithm.
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12

Popov, D. I. "The adaptive notch filter with complex weights." Journal of «Almaz – Antey» Air and Space Defence Corporation, no. 2 (June 30, 2015): 21–26. http://dx.doi.org/10.38013/2542-0542-2015-2-21-26.

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Considered the criteria and algorithms to adapt FIR notch filters to the unknown spectral-correlation characteristics of clutter. On the basis of approximate models obtained clutter stable computationally adaptive algorithms of filtration data interference. The block diagram of adaptive notch filters and sliding batch processing.
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13

Zhang, Jie. "Application of Quantum Particle Swarm Optimization in Adaptive Notch Filter Design." Advanced Materials Research 482-484 (February 2012): 2466–69. http://dx.doi.org/10.4028/www.scientific.net/amr.482-484.2466.

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Abstract: adaptive notch filter is a kind of apparatus which can eliminate single frequency or narrow-band interference, normal adaptive algorithm of notch filter is LMS algorithm, but the faster convergence velocity and the smaller steady error are difficult to gain simultaneously. Aimed at the weakness of LMS, the Particle Swarm Optimization (PSO) is studied deeply in the paper, based on the PSO; the quantum mechanic theory is added to improve it. Quantum Particle Swarm Optimization (QPSO) is researched and applied for adaptive notch filter which is proved more efficient in the noise control by MATLAB simulation. The new QPSO algorithm can balance the maladjustment and the searching ability of adaptive filter with a little calculation, the speed of convergence is faster than LMS and normal PSO algorithm.
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14

CHICHARO, JOE F., and TUNG S. NG. "Tunable/adaptive second-order IIR notch filter." International Journal of Electronics 68, no. 5 (May 1990): 779–92. http://dx.doi.org/10.1080/00207219008921219.

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15

Strobach, P. "Single section least squares adaptive notch filter." IEEE Transactions on Signal Processing 43, no. 8 (1995): 2007–10. http://dx.doi.org/10.1109/78.403365.

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16

Kobayashi, Masaki, Naoto Sasaoka, Yasutomo Kinugasa, Kazuki Shiogai, and Yoshio Itoh. "A Cascaded SSCF-IIR Adaptive Notch Filter." IEEJ Transactions on Electronics, Information and Systems 138, no. 7 (July 1, 2018): 934–40. http://dx.doi.org/10.1541/ieejeiss.138.934.

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17

Chen, Bor-Sen, Tsang-Yi Yang, and Bin-Hong Lin. "Adaptive notch filter by direct frequency estimation." Signal Processing 27, no. 2 (May 1992): 161–76. http://dx.doi.org/10.1016/0165-1684(92)90005-h.

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18

Nakamura, Youhei, Arata Kawamura, and Youji Iiguni. "An Adaptive Notch Gain Using an Inverse Notch Filter and a Linear Prediction Filter." IEEJ Transactions on Electronics, Information and Systems 136, no. 2 (2016): 108–15. http://dx.doi.org/10.1541/ieejeiss.136.108.

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19

NAKAMURA, YOUHEI, ARATA KAWAMURA, and YOUJI IIGUNI. "An Adaptive Notch Gain Using an Inverse Notch Filter and a Linear Prediction Filter." Electronics and Communications in Japan 100, no. 2 (January 9, 2017): 58–67. http://dx.doi.org/10.1002/ecj.11935.

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20

Elmelhi, Ali. "Modified Adaptive Notch Filter Based on Neural Network for Flexible Dynamic Control." International Journal of Computer and Electrical Engineering 6, no. 2 (2014): 185–90. http://dx.doi.org/10.7763/ijcee.2014.v6.819.

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21

Liu, Jin Chun, Qi Wei He, and Shi Jian Zhu. "Adaptive Detection of Sinusoidal Signal Based on Adaptive Iir Notch Filter." Advanced Materials Research 482-484 (February 2012): 541–45. http://dx.doi.org/10.4028/www.scientific.net/amr.482-484.541.

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Adaptive tracking sinusoidal signals with time-varying frequency buried in white noise presents a great interest in engineering applications. A simple approach of application of adaptive notch filters (ANFs) in recursive identification was presented. The use of adaptive infinite impulse response (IIR) notch filters is exploited to detect the sinusoidal components in noise as far as the two-stage vibration isolation system. Computer simulations and experiments on real signals generated by the two-stage system vibration isolation demonstrate the advantage of this method in terms of estimation variance, convergence speed, and the capability of tracking the signals.
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22

LIANG, HONG, XIAOWEI LI, and XIANG-GEN XIA. "ADAPTIVE FREQUENCY ESTIMATION WITH LOW SAMPLING RATES BASED ON ROBUST CHINESE REMAINDER THEOREM AND IIR NOTCH FILTER." Advances in Adaptive Data Analysis 01, no. 04 (October 2009): 587–600. http://dx.doi.org/10.1142/s1793536909000230.

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In this paper, based on an adaptive IIR notch filter and a robust Chinese remainder theorem (CRT), we propose an adaptive frequency estimation algorithm from multiple undersampled sinusoidal signals. Our proposed algorithm can significantly reduce the sampling rates and provide more accurate estimates than the method based on adaptive IIR notch filter and sampling rates above the Nyquist rates does. We then present simulation results to verify the performance of our proposed algorithm for both stationary and nonstationary signals.
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23

Hidayat, Rahmad, Ninik Sri Lestari, Herawati Herawati, Givy Devira Ramady, Sudarmanto Sudarmanto, and Farhan Adani. "An approach of adaptive notch filtering design for electrocardiogram noise cancellation." Indonesian Journal of Electrical Engineering and Computer Science 22, no. 3 (June 1, 2021): 1303. http://dx.doi.org/10.11591/ijeecs.v22.i3.pp1303-1311.

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An electrocardiogram (ECG) is a means of measuring and monitoring important signals from heart activity. One of the major biomedical signal issues such as ECG is the issue of separating the desired signal from noise or interference. Different kinds of digital filters are used to distinguish the signal components from the unwanted frequency range to the ECG signal. To address the question of noise to the ECG signal, in this paper the digital notch filter IIR 47 Hz is designed and simulated to demonstrate the elimination of 47 Hz noise to obtain an accurate ECG signal. The full architecture of the structure and coefficient of the IIR notch filter was carried out using the FDA Tool. Then the model is finished with the help of Simulink and the MATLAB script was to filter out the 47 Hz noise from the signal of ECG. For this purpose, the normalized least mean square (NLMS) algorithm was used. The results indicate that before being filtered and after being filtered it clearly shows the elimination of 47 Hz noise in the signal of the ECG. These results also show the accuracy of the design technique and provide an easy model to filter out noise in the ECG signal.
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24

CHU, Zhao-Bi, Chong-Wei ZHANG, and Xiao-Ying FENG. "Adaptive Notch Filter-based Frequency and Amplitude Estimation." Acta Automatica Sinica 36, no. 1 (April 19, 2010): 60–66. http://dx.doi.org/10.3724/sp.j.1004.2010.00060.

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25

Abbas, M. K., M. Mokhtar, M. I. Marei, and A. A. El-Sattar. "Adaptive Notch Filter based WECS for Unbalance Mitigation." Renewable Energy and Power Quality Journal 19 (September 2021): 362–67. http://dx.doi.org/10.24084/repqj19.295.

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The accelerating spread of distributed energy resources among the LV networks has revealed their adverse impact on voltage profiles, power quality and protections along the network. On the contrary, since they are essentially interfaced with the network through power electronic converters that can be exploited to enhance power quality. Voltage regulation, unbalance and harmonics mitigation are some examples of the functions that can be implemented through these converters. This paper presents a wind energy conversion system (WECS) with a back-to-back converter performing its mere function of maximizing wind energy capture and regulating output active and reactive power. Added to these basic functions, ancillary services are provided to a local load and MV grid. Voltage regulation of the load voltage at different loading conditions is achieved. Extraction of load unbalance is investigated through different algorithms. Adaptive Notch Filter (ANF) has demonstrated a leading response over the conventional methods in detecting the symmetrical components under different unbalance conditions. Unbalance in grid currents is then effectively managed and the currents from/to the MV grid are ensured to be balanced. The system is simulated using PSCAD/EMTDC and results are presented to confirm validity of the proposed methods.
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26

Niedźwiecki, Maciej, and Adam Sobociński. "SELF-OPTIMIZING REAL-VALUED GENERALIZED ADAPTIVE NOTCH FILTER." IFAC Proceedings Volumes 42, no. 10 (2009): 438–43. http://dx.doi.org/10.3182/20090706-3-fr-2004.00072.

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27

SUGIURA, Yosuke, Arata KAWAMURA, and Youji IIGUNI. "An Adaptive Comb Filter with Flexible Notch Gain." IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences E95.A, no. 11 (2012): 2046–48. http://dx.doi.org/10.1587/transfun.e95.a.2046.

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28

Kobayashi, Masaki. "Noise Free Second Order IIR Adaptive Notch Filter." IEEJ Transactions on Electronics, Information and Systems 134, no. 10 (2014): 1586–87. http://dx.doi.org/10.1541/ieejeiss.134.1586.

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29

Nam Ik Cho and Sang Uk Lee. "Tracking analysis of an adaptive lattice notch filter." IEEE Transactions on Circuits and Systems II: Analog and Digital Signal Processing 42, no. 3 (March 1995): 186–95. http://dx.doi.org/10.1109/82.372868.

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30

Regalia, P. A. "An improved lattice-based adaptive IIR notch filter." IEEE Transactions on Signal Processing 39, no. 9 (1991): 2124–28. http://dx.doi.org/10.1109/78.134453.

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31

Dragosevic, M. V., and S. S. Stankovic. "An adaptive notch filter with improved tracking properties." IEEE Transactions on Signal Processing 43, no. 9 (1995): 2068–78. http://dx.doi.org/10.1109/78.414768.

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32

Conolly, S., and Young-Lim Su. "State-space analysis of the adaptive notch filter." Proceedings of the IEEE 74, no. 1 (1986): 219–21. http://dx.doi.org/10.1109/proc.1986.13436.

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33

Niedzwiecki, M., and P. Kaczmarek. "Tracking analysis of a generalized adaptive notch filter." IEEE Transactions on Signal Processing 54, no. 1 (January 2006): 304–14. http://dx.doi.org/10.1109/tsp.2005.861087.

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34

Mojiri, Mohsen, Masoud Karimi-Ghartemani, and Alireza Bakhshai. "Time-Domain Signal Analysis Using Adaptive Notch Filter." IEEE Transactions on Signal Processing 55, no. 1 (January 2007): 85–93. http://dx.doi.org/10.1109/tsp.2006.885686.

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35

Verma, A. R., and Y. Singh. "Adaptive Tunable Notch Filter for ECG Signal Enhancement." Procedia Computer Science 57 (2015): 332–37. http://dx.doi.org/10.1016/j.procs.2015.07.347.

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36

Mojiri, M., and A. R. Bakhshai. "Estimation of $n$ Frequencies Using Adaptive Notch Filter." IEEE Transactions on Circuits and Systems II: Express Briefs 54, no. 4 (April 2007): 338–42. http://dx.doi.org/10.1109/tcsii.2006.889724.

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37

Levin, Jason, Néstor O. Perez-Arancibia, and Petros A. Ioannou. "Adaptive Notch Filter Using Real-Time Parameter Estimation." IEEE Transactions on Control Systems Technology 19, no. 3 (May 2011): 673–81. http://dx.doi.org/10.1109/tcst.2010.2049493.

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38

Wang, Qiusheng, Xiaolan Gu, and Jinyong Lin. "Adaptive notch filter design under multiple identical bandwidths." AEU - International Journal of Electronics and Communications 82 (December 2017): 202–10. http://dx.doi.org/10.1016/j.aeue.2017.08.054.

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39

Ahammed, Kawser. "Removal of Structured Noise and Base Line Wander From ECG Signals via LMS Adaptive and Fixed Notch Filter." European Journal of Engineering Research and Science 3, no. 8 (August 13, 2018): 12. http://dx.doi.org/10.24018/ejers.2018.3.8.830.

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This research clearly demonstrates the comparative performance study of Least Mean Square (LMS) adaptive and fixed Notch filter in terms of simulation results and different performance parameters (mean square error, signal to noise ratio and percentage root mean square difference) for removing structured noise (50 Hz line interference and its harmonics) and baseline wandering from electrocardiogram (ECG) signal. The ECG samples collected from the PhysioNet ECG-ID database are corrupted by adding structured noise and base line wandering noise. The simulation results and numerical performance analysis of this research clearly show that LMS adaptive filter can remove noise efficiently from ECG signal than fixed notch filter
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40

Ahammed, Kawser. "Removal of Structured Noise and Base Line Wander From ECG Signals via LMS Adaptive and Fixed Notch Filter." European Journal of Engineering and Technology Research 3, no. 8 (August 13, 2018): 12–15. http://dx.doi.org/10.24018/ejeng.2018.3.8.830.

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This research clearly demonstrates the comparative performance study of Least Mean Square (LMS) adaptive and fixed Notch filter in terms of simulation results and different performance parameters (mean square error, signal to noise ratio and percentage root mean square difference) for removing structured noise (50 Hz line interference and its harmonics) and baseline wandering from electrocardiogram (ECG) signal. The ECG samples collected from the PhysioNet ECG-ID database are corrupted by adding structured noise and base line wandering noise. The simulation results and numerical performance analysis of this research clearly show that LMS adaptive filter can remove noise efficiently from ECG signal than fixed notch filter
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41

Ziatdinov, Sergey, and Leonid Osipov. "Suppression of correlated interference by adaptive notch filters under pulse repetition period modulation." Information and Control Systems, no. 3 (June 29, 2021): 53–60. http://dx.doi.org/10.31799/1684-8853-2021-3-53-60.

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Introduction: We discuss the problem of correlated noise suppression by adaptive complex notch filters of various orders. In order to eliminate the dependence of the transmission coefficient of the useful signal on its frequency, the pulse repetition period is modulated. Purpose: Studying the influence of pulse repetition period modulation on the correlated noise suppression coefficient. Methods: The notch filter parameters were optimized with the criterion of minimum average dispersion of correlated noise at the output of the filters during the repetition period modulation. Results: Expressions are obtained for the variance of correlated noise at the output of complex adaptive filters of various orders when the repetition period is modulated. Relationships are given for finding the optimal values ​​of the tuning frequency and coefficients of the notch filters which minimize the correlated noise level at their output. Expressions are obtained for the coefficients of correlated noise suppression by notch filters in the context of pulse repetition period modulation. The graphs are presented showing how the correlated noise suppression coefficient depends on the relative value of the probing signal repetition period deviation for various values ​​of the correlated noise spectral density width at optimal or non-optimal values ​​of the tuning frequency and coefficients of the notch filters. It is shown that the use of probing pulse repetition period modulation leads to a decrease in the correlated noise suppression coefficient. On the other hand, the adaptation of the weighting coefficients for the adopted models of notch filters and correlated interference provides an increase in the suppression coefficient. Practical relevance: When developing or studying correlated noise suppression systems, the obtained results make it possible, taking into account the permissible losses of the suppression coefficient, to reasonably choose the input pulse repetition period deviation value in order to eliminate the effect of “blind” frequencies.
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42

Zheng, Min Ying, Wan Neng Yu, and Yi Qun Xu. "The Modeling Study of Active Power Filter Based on Adaptive Notch Filter." Advanced Materials Research 418-420 (December 2011): 1906–10. http://dx.doi.org/10.4028/www.scientific.net/amr.418-420.1906.

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Aiming at small power grid’s influencing on the frequency stabilization of the power grid when load’s large change, the basic development present situation and work principle of active power filter are analyzed at first. Then combining active filter’s control strategy based on instantaneous reactive power and hysteresis current, the active filter simulation model about grid frequency’s change is established according to studying the method of using adaptive notch filter to measure power frequency. Finally, the simulation results prove that the active power filter model could track the changing frequency quickly and compensate harmonic current accurately, and enhance power quality and reliability of the small power grid.
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43

Wang, Yong, Qiangang Zheng, Haibo Zhang, and Haoying Chen. "Research on predictive control of helicopter/engine based on LMS adaptive torsional vibration suppression." Journal of Low Frequency Noise, Vibration and Active Control 37, no. 4 (August 19, 2018): 1151–63. http://dx.doi.org/10.1177/1461348418790495.

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In order to achieve the fast response of turboshaft engine combined with torsional vibration, a predictive controller of helicopter/engine based on the least mean square adaptive torsional vibration suppression is proposed and designed. First, in order to make up for the insufficiency of conventional notch filter on torsional vibration suppression with changeable frequency under variable rotor speed, an adaptive one based on least mean square is presented in the process of helicopter autorotation downward. Then, based on the least mean square adaptive filter, a predictive controller based on the support vector regression is proposed to compensate for the dynamic control performance in helicopter autorotation recovery process. It is shown that least mean square adaptive filter can suppress all low-order torsional vibrations with amplitude less than 15% in comparison with the notch filter, which proves the more remarkable ability of adaptive torsional vibration suppression. Meanwhile, the droop of power turbine speed can be reduced to less than 0.3% with the steady-state error no more than 0.01% by adopting the predictive controller based on least mean square adaptive torsional vibration suppression. The fast response and high-quality control of turboshaft engine has been realized.
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44

Loedwassana, Wuthiporn. "Performance Comparison of a Second-order adaptive IIR Notch Filter based on Plain Gradient Algorithm." ECTI Transactions on Electrical Engineering, Electronics, and Communications 15, no. 1 (November 8, 2016): 41–48. http://dx.doi.org/10.37936/ecti-eec.2017151.171290.

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This paper presents performance analysis of a second-order adaptive IIR notch filter with constrained poles and zeros in direct form II structure that is adapted by algorithms of indirect and direct frequency estimations based on plain gradient. In this work, the steady-state bias properties and stability bounds of both algorithms are derived in closed form. The simulated processes are performed in order to verify the analytical results. Furthermore, these results of the proposed filter are also compared with those results of the direct form I adaptive IIR notch filter under the same parameters. It has been revealed that the direct form II structure has given the steady-state performance over the direct form I structure.
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45

SUGIURA, Yosuke, Arata KAWAMURA, and Youji IIGUNI. "A Comb Filter with Adaptive Notch Gain and Bandwidth." IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences E96.A, no. 4 (2013): 790–95. http://dx.doi.org/10.1587/transfun.e96.a.790.

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46

Yin, Guiliang, Lei Guo, and Xiangnan Li. "An Amplitude Adaptive Notch Filter for Grid Signal Processing." IEEE Transactions on Power Electronics 28, no. 6 (June 2013): 2638–41. http://dx.doi.org/10.1109/tpel.2012.2226752.

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47

Soo-Chang Pei and Chien-Cheng Tseng. "Complex adaptive IIR notch filter algorithm and its applications." IEEE Transactions on Circuits and Systems II: Analog and Digital Signal Processing 41, no. 2 (1994): 158–63. http://dx.doi.org/10.1109/82.281849.

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48

Peng, Renhua, Chengshi Zheng, and Xiaodong Li. "Two‐stage optimisation algorithm for adaptive IIR notch filter." Electronics Letters 50, no. 14 (July 2014): 985–87. http://dx.doi.org/10.1049/el.2014.0676.

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49

Morgan, D. R., and J. Thi. "A multitone pseudocascade, filtered-X LMS adaptive notch filter." IEEE Transactions on Signal Processing 41, no. 2 (1993): 946–56. http://dx.doi.org/10.1109/78.193233.

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50

Ra, W. S. "Practical adaptive notch filter for missile bending mode rejection." Electronics Letters 41, no. 5 (2005): 228. http://dx.doi.org/10.1049/el:20057263.

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