Identyfikatory
Warianty tytułu
Języki publikacji
Abstrakty
In this paper, Recursive Least Square (RLS) and Affine Projection (AP) adaptive filters are designed using Xilinx System Generator and implemented on the Spartan6 xc6slx16- 2csg324 FPGA platform. FPGA platform utilizes the non-restoring division algorithm and the COordinate Rotation DIgital Computer (CORDIC) division algorithm to perform the division task of the RLS and AP adaptive filters. The Non-restoring division algorithm demonstrates efficient performance in terms of convergence speed and signal-to-noise ratio. In contrast, the CORDIC division algorithm requires 31 cycles for division initialization, whereas the non-restoring algorithm initializes division in just one cycle. To validate the effectiveness of the proposed filters, a set of ten ECG records from the BIT-MIT database is used to test their ability to remove Power Line Interference (PLI) noise from the ECG signal. The proposed adaptive filters are compared with various adaptive algorithms in terms of Signal-to-Noise Ratio (SNR), convergence speed, residual noise, steady-state Mean Square Error (MSE), and complexity.
Słowa kluczowe
Rocznik
Tom
Strony
811--817
Opis fizyczny
Bibliogr. 18 poz., tab., wykr.
Twórcy
autor
- University ofTechnology, Iraq
autor
- University ofTechnology, Iraq
Bibliografia
- [1] T. T. Hasan, M. H. Jasim, I. A. Hashim. FPGA Design and Hardware Implementation of Heart Disease Diagnosis System Based on NVG-RAM Classifier, 2018 Third Scientific Conference of Electrical Engineering (SCEE), 2018, pp. 33-38, http://doi.org/10.1109/SCEE.2018.8684125
- [2] A. Z. Khan, I. Shafi . Removing Artifacts from Raw Electrocardiogram Signals Using Adaptive Filter in State Space. Circuits Syst Signal Process, 1713 (2020). http://doi.org/10.1007/s00034-019-01149-3
- [3] T. M. Jamel, K. K. Al-Magazachi KK, Simple variable step size LMS algorithm for adaptive identification of IIR filtering system, The 5th International Conference on Communications, Computers and Applications (MIC-CCA2012), 2012, pp. 23-28.
- [4] M. Kazemi, M. M. Arefi. A fast iterative recursive least squares algorithm for Wiener model identification of highly nonlinear systems, ISA Transactions, Volume 67, 2017, Pages 382-388, http://doi.org/10.1016/j.isatra.2016.12.002
- [5] A. O. Abid Noor. Adaptive Noise Cancellation Using Noise Dependent Affine Projection Algorithm, Engineering and Technology Journal, Vol. 35, Part A, No. 6, 2017.
- [6] G. Swaminathan, G. Murugesan, S. Sasikala, L. Murali. A novel implementation of combined systolic and folded architectures for adaptive filters in FPGA, Microprocessors and Microsystems, Volume 74, 2020, http://doi.org/10.1016/j.micpro.2020.103018
- [7] M. Jayapravintha, S. Gomathi, G. Murugesan. Design of Systolic architecture for various adaptive filters for noise cancellation, 2015 3rd International Conference on Signal Processing, Communication and Networking (ICSCN), Chennai, India, 2015, pp. 1-6, http://doi.org/10.1109/ICSCN.2015.7219907
- [8] V. Kavitha, P. K. Priya, Tha. Sugapriyaa. Efficient Implementation of Adaptive Filter Architecture Using Gate Level Modification for ECG Denoising," Proceedings of 2018 the 8th International Workshop on Computer Science and Engineering, pp. 171-177, Bangkok, 28-30 June, 2018, http://doi.org/10.18178/wcse.2018.06.031
- [9] M. Chandra, P. Goel, A. Anand, A. Kar. Design and analysis of improved high-speed adaptive filter architectures for ECG signal denoising, Biomedical Signal Processing and Control, Volume 63, 2021, http://doi.org/10.1016/j.bspc.2020.102221
- [10] S. C., S. S., M.G. Denoising ECG signal using combination of ENSLMS and ZA-LMS algorithms, 3rd International Conference on Signal Processing, Communication and Networking (ICSCN), 2015, pp. 1-6.
- [11] S. Veni, “Real Time Implementation of SIGN LMS Adaptive Filters using Xilinx System Generator,” International Journal of Mathematics and Computers in Simulation, vol. 14, 2020.
- [12] S. Jayapoorani, D. Pandey, N. S. Sasirekha, et al, “Systolic optimized adaptive filter architecture designs for ECG noise cancellation by Vertex-5. AS 6,” 163-173 (2023). http://doi.org/10.1007/s42401-022-00177-3
- [13] F. Salehi, E. Farshidi, H. Kaabi. Novel design for a low-latency CORDIC algorithm for sine-cosine computation and its Implementation on FPGA, Microprocessors and Microsystems, Volume 77, 2020, 103197, ISSN 0141-9331, https://doi.org/10.1016/j.micpro.2020.103197
- [14] R. S. Hongal, D. J. Anita. Comparative Study of Different Division Algorithms for Fixed and Floating Point Arithmetic Unit for Embedded Applications, 2016.
- [15] F. Ding, Y. Wang, J. Ding. Recursive least squares parameter identification algorithms for systems with colored noise using the filtering technique and the auxilary model, Digital Signal Processing, Volume 37, 2015, Pages 100-108, http://doi.org/10.1016/j.dsp.2014.10.005
- [16] Y. Hu. Iterative and recursive least squares estimation algorithms for moving average systems, Simulation Modelling Practice and Theory, Volume 34, 2013, Pages 12-19, http://doi.org/10.1016/j.simpat.2012.12.009
- [17] D. Liu, H. Zhao.Affine Projection Sign Subband Adaptive Filter Algorithm With Unbiased Estimation Under System Identification, in IEEE Transactions on Circuits and Systems II: Express Briefs, vol. 70, no. 3, pp. 1209-1213, March 2023, http://doi.org/10.1109/TCSII.2022.3216807
- [18] Y. Ren, Y. Zhi, J. Zhang. Geometric-algebra affine projection adaptive filter, EURASIP J. Adv. Signal Process. 2021, 82 (2021). http://doi.org/10.1186/s13634-021-00790-y
Uwagi
Opracowanie rekordu ze środków MNiSW, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2024).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-05c13eaf-176a-40f1-adf7-63ff4827efab