Devarajan, Rajasegaran (2022) Digital filtering optimization on noisy human speech in assistive listening system. College of Engineering, Universiti Malaysia Pahang.
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EA18028_Devarajan_Thesis - deva rajan.pdf - Accepted Version Download (1MB) | Preview |
Abstract
This paper represents the acoustic noise cancellation system by adaptive filter algorithms. The adaptive algorithms are least mean square (LMS), Normalized least mean square (NLMS) and recursive least square (RLS). This paper investigates the execution of LMS, NLMS and RLS calculations for acoustic noise by running the model continuously for sound signs and signal processing. The fundamental is on the utilization of NLMS and RLS calculations to lessen undesirable noise or commotion hence increasing desired sound signal quality. MATLAB Simulink method is being utilized for simulation. Adaptive filter is usually utilized for the undoing of the noise part which is blended with the wanted sound sign. LMS is generally utilized because of its effortlessness and robustness, however it neglects to finish merging criteria so here LMS is improvised by NLMS which is a sort of LMS algorithm and we additionally tried for the RLS which shows significant improvement. RLS shows better exhibitions and it has speedier meeting speed/rate than LMS and NLMS calculations with better strength to alterable environment and better following ability and almost can get clear speech signal.
| Item Type: | Undergraduates Project Papers |
|---|---|
| Additional Information: | SV: Ts. Dr. Roshahliza binti M Ramli |
| Uncontrolled Keywords: | Digital filtering, assistive listening system |
| Subjects: | T Technology > TA Engineering (General). Civil engineering (General) T Technology > TK Electrical engineering. Electronics Nuclear engineering |
| Faculty/Division: | College of Engineering |
| Depositing User: | Mr. Nik Ahmad Nasyrun Nik Abd Malik |
| Date Deposited: | 24 Oct 2023 07:43 |
| Last Modified: | 24 Oct 2023 07:43 |
| URI: | http://umpir.ump.edu.my/id/eprint/39004 |
| Download Statistic: | View Download Statistics |
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