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...
| Autor Principal: | Jiménez-López, Fabián Rolando; M. Sc. Research Digital Signal Processing Group Universidad Pedagógica y Tecnológica de Colombia Tunja, |
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| Otros Autores: | Pardo-Beainy, Camilo Ernesto; M. Sc. (c)., Research and Development Engineering in new Technologies Group Universidad Santo Tomas Tunja,, Gutiérrez-Cáceres, Edgar Andrés; M. Sc. (c)., Research and Development Engineering in new Technologies Group Universidad Santo Tomas Tunja, |
| Formato: | info:eu-repo/semantics/article |
| Idioma: | spa |
| Publicado: |
Universidad Santo Tomás. Seccional Bucaramanga
2014
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| Materias: | |
| Acceso en línea: |
http://revistas.ustabuca.edu.co/index.php/ITECKNE/article/view/726 |
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| Sumario: |
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. |
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