Adaptive filtering implemented over TMS320c6713 DSP platform for system identification
This paper presents the experimental development of software and hardware configuration to implement two adaptive algorithms: LMS (Least Mean Square) and RLS (Recursive Least Square), using TMS320C6713 DSP platform of Texas Instruments, for unknown systems identification. Methodology for implementat...
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| Veröffentlicht in: | Iteckne 2014-12, Vol.11 (2), p.157-171 |
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| container_title | Iteckne |
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| creator | Jiménez-López, Fabián Rolando Pardo-Beainy, Camilo Ernesto Gutiérrez-Cáceres, Edgar Andrés |
| description | This paper presents the experimental development of software and hardware configuration to implement two adaptive algorithms: LMS (Least Mean Square) and RLS (Recursive Least Square), using TMS320C6713 DSP platform of Texas Instruments, for unknown systems identification. Methodology for implementation and validation analysis for the adaptive algorithms is described in detail for real-time systems identification applications, and the experimental results were evaluated in terms of performance criterions in time domain, frequency domain, computational complexity, and accuracy. |
| doi_str_mv | 10.15332/iteckne.v11i2.726 |
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| subjects | Adaptive Filtering Digital Signal Processor ENGINEERING, MULTIDISCIPLINARY LMS Algorithm Real Time Processing RLS Algorithm System Identification |
| title | Adaptive filtering implemented over TMS320c6713 DSP platform for system identification |
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