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Linea/s de investigación:

SOUND-PROCESSING ALGORITHMS WITH PHYSIC-INFORMED MACHINE LEARNING TOOLS FOR SOUND-FIELD SYNTHESIS ENTIDAD FINANCIADORA: AGENCIA ESTATAL DE INVESTIGACION. PID2024-161353OB AÑOS DE VIGENCIA: 2025-2028 INVESTIGADOR PRINCIPAL: Alberto Gonzalez, Miguel Ferrer N° DE INVESTIGADORES: 8 ENLACE:

Resumen

SAPIENS-CONTROL pioneers the integration of Physics-Informed Machine Learning (PIML) into sound signal processing, particularly in Active Noise Control (ANC), adaptive filtering, and speech masking. PIML incorporates physical acoustics principles into learning models, enhancing accuracy, generalization, and efficiency. This research pushes PIML boundaries by embedding physical knowledge into data-driven models, optimizing adaptive filtering, and refining neural architectures for real-time acoustic processing.

Para mas información sobre el mismo, consultar el enlace del proyecto.