### ADAPTIVE METHOD TO PREDICT AND TRACK UNKNOWN SYSTEM BEHAVIORS USING RLS AND LMS ALGORITHMS

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L. M. Dogariu, S. Ciochină, C. Paleologu, J. Benesty, and P. Piantanida, "An adaptive solution for nonlinear system identification", In Proceedings of the International Symposium on Signals, Circuits and Systems (ISSCS), Iasi, Romania, 2017, pp. 1-4.

P. Kshirsagar, D. Jiang, and Z. Zhang, "Implementation and Evaluation of Online System Identification of Electromechanical Systems Using Adaptive Filters", IEEE Trans. Ind. Appl., vol. 52, no. 3, pp. 2306-2314, 2016.

A. Abid, M. T. Khan, H. Lang, and C. W. d. Silva, "Adaptive System Identification and Severity Index-Based Fault Diagnosis in Motors", IEEE/ASME Trans. Mechatron., vol. 24, no. 4, pp. 1628-1639, 2019.

S. Ciochină, C. Paleologu, J. Benesty, S. L. Grant, and A. Anghel, "A family of optimized LMS-based algorithms for system identification", In Proceedings of the 24th European Signal Processing Conference (EUSIPCO), Budapest, Hungary, 2016, pp. 1803-1807.

F. Ding, X. Liu, and M. Liu, "The recursive least squares identification algorithm for a class of Wiener nonlinear systems", J. Franklin Inst., vol. 353, no. 7, pp. 1518-1526, 2016.

M. T. M. Silva, R. Candido, J. Arenas-Garcia, and L. A. Azpicueta-Ruiz, "Improving Multikernel Adaptive Filtering with Selective Bias", In Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Calgary, AB, 2018, pp. 4529-4533.

S. R. Prasad and S. A. Patil, "Implementation of LMS algorithm for system identification", In Proceedings of the International Conference on Signal and Information Processing (IConSIP), Vishnupuri, 2016, pp. 1-5.

S. Mukhopadhyay and A. Mukherjee, "ImdLMS: An Imputation Based LMS Algorithm for Linear System Identification With Missing Input Data", IEEE Trans. Signal Process., vol. 68, pp. 2370-2385, 2020.

Y. Li, Y. Wang, and T. Jiang, "Sparse least mean mixed-norm adaptive filtering algorithms for sparse channel estimation applications", Int. J. Commun. Syst., vol. 30, no. 8, p. e3181, 2017.

W. Ma, X. Qiu, J. Duan, Y. Li, and B. Chen, "Kernel recursive generalized mixed norm algorithm", J. Franklin Ins., vol. 355, no. 4, pp. 1596-1613, 2018.

G. Eleyan and M. S. Salman, "Convergence analysis of the mixed-norm LMS and two versions for sparse system identification", Signal, Image and Video Processing, vol. 14, no. 5, pp. 965-970, 2020.

L.-M. Dogariu, S. Ciochină, J. Benesty, and C. Paleologu, "System Identification Based on Tensor Decompositions: A Trilinear Approach", Symmetry, vol. 11, no. 4, p. 556, 2019.

F. Ding and T. Chen, "Identification of Hammerstein nonlinear ARMAX systems", Automatica, vol. 41, no. 9, pp. 1479-1489, 2005.

F. Ding, X. Wang, Q. Chen, and Y. Xiao, "Recursive Least Squares Parameter Estimation for a Class of Output Nonlinear Systems Based on the Model Decomposition", Circ. Syst. Signal Pr., vol. 35, no. 9, pp. 3323-3338, 2016.

P. Mattsson, D. Zachariah, and P. Stoica, "Recursive nonlinear-system identification using latent variables", Automatica, vol. 93, pp. 343-351, 2018.

P. Mattsson, D. Zachariah, and P. Stoica, "Identification of cascade water tanks using a PWARX model", Mech. Syst. Signal Process., vol. 106, pp. 40-48, 2018.

C. Elisei-Iliescu, C. Paleologu, C. Stanciu, C. Anghel, S. Ciochină, and J. Benesty, "Regularized Recursive Least-Squares Algorithms for the Identification of Bilinear Forms", In Proceedings of the International Symposium on Electronics and Telecommunications (ISETC), Timisoara, 2018, pp. 1-4.

C. Elisei-Iliescu, C. Stanciu, C. Paleologu, J. Benesty, C. Anghel, and S. Ciochină, "Efficient recursive least-squares algorithms for the identification of bilinear forms", Digit. Signal Process., vol. 83, pp. 280-296, 2018.

A. D. Poularikas, "The Least Mean Square Algorithm", in Adaptive Filtering Fundementals of Least Mean Squares with MatlabUnited State of America: CRC Press, 2015, pp. 203-232.

L. Tan and J. Jiang, "Adaptive filters and aplications", in Digital Signal Processing Fundamentals and Applications 3rd ed. USA: Academic Press, 2019, pp. 421-474.

R. J. Schilling and S. L. Harris, "Adaptive Signal Processing", in Digital Signal Processing Using MATLABUnited States of America: Cengage Learning, 2017, pp. 667-760.

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