Optimization of Rls Adaptive Filter Architecture Using Gate Level Modification for Clamor Cancellation
P. Kaviya Priya1, V. Kaviyasree2, S. Mahalakshmi3, M. Mohanapriya4
1P.Kaviya Priya, Assistant Professor, Department of Electronics and Communication Engineering, M. Kumarasamy College of Engineering, Karur (Tamil Nadu), India.
2V.Kaviyasree, UG Scholar, Department of Electronics and Communication Engineering, M. Kumarasamy College of Engineering, Karur (Tamil Nadu), India.
3S.Mahalakshmi, UG Scholar, Department of Electronics and Communication Engineering, M. Kumarasamy College of Engineering, Karur (Tamil Nadu), India.
4M.Mohanapriya, UG Scholar, Department of Electronics and Communication Engineering, M. Kumarasamy College of Engineering, Karur (Tamil Nadu), India.
Manuscript received on 25 May 2019 | Revised Manuscript received on 03 June 2019 | Manuscript Published on 22 June 2019 | PP: 339-343 | Volume-8 Issue-3S, February 2019 | Retrieval Number: C10690283S19/19©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: An adaptive filter constitutes a major part in the noise cancellation application. In this paper, we introduce associativity technique instead of conventional technique using MatLab Simulink. Recursive least square is an adaptive algorithm that periodically finds the coefficients that modify a weighted linear squares cost function according to the input signals. The proposed method shows better enhancement in LUT respectively. From the results, it is clear that Associativity technique shows LUT reduced by 77.14% than that of Conventional technique for 8 tap FIR Filter and it is reduced by 12.8% than that of Conventional technique respectively.
Keywords: Adaptive Filter, Associativity, LUT, RLS, SNR.
Scope of the Article: Discrete Optimization