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En tant que problème spécial d'estimation de fréquence, l'estimation des harmoniques a des applications dans le traitement de la parole et de l'audio, les systèmes d'alimentation, la surveillance des soins de santé, etc. Dans cet article, nous faisons une première tentative pour proposer une méthode clairsemée sans grille pour l'estimation des harmoniques exploitant la structure des harmoniques. La méthode utilise la norme atomique avec des atomes soigneusement conçus et est formulée comme un problème d'optimisation convexe. Sa performance est démontrée par des simulations numériques.
Como problema especial de estimación de frecuencia, la estimación de armónicos tiene aplicaciones en el procesamiento de voz y audio, sistemas de alimentación, monitoreo de atención médica, etc. En este artículo, hacemos un primer intento de proponer un método escaso sin rejilla para la estimación de armónicos aprovechando la estructura de armónicos. El método utiliza la norma atómica con átomos cuidadosamente diseñados y se formula como un problema de optimización convexo. Su rendimiento se demuestra a través de simulaciones numéricas.
As a special frequency estimation problem, harmonics estimation has applications in speech and audio processing, power systems, healthcare monitoring, etc. In this paper, we make a first attempt to propose a gridless sparse method for harmonics estimation exploiting the harmonics structure. The method uses the atomic norm with carefully designed atoms and is formulated as a convex optimization problem. Its performance is demonstrated via numerical simulations.
كمشكلة خاصة في تقدير التردد، فإن تقدير التوافقيات له تطبيقات في معالجة الكلام والصوت، وأنظمة الطاقة، ومراقبة الرعاية الصحية، إلخ. في هذه الورقة، نقوم بمحاولة أولى لاقتراح طريقة متفرقة بدون شبكة لتقدير التوافقيات باستغلال بنية التوافقيات. تستخدم الطريقة المعيار الذري مع الذرات المصممة بعناية وتتم صياغتها كمشكلة تحسين محدبة. يظهر أدائها من خلال المحاكاة العددية.
Artificial intelligence, Sparse System Identification, Physics, Harmonics, Computational Mechanics, Voltage, Computer science, Quantum mechanics, Resolution (logic), Engineering, Adaptive Filtering in Non-Gaussian Signal Processing, Computer Science, Physical Sciences, Signal Processing, Computer Vision and Pattern Recognition, Image Denoising Techniques and Algorithms, Sparse Representations, Speech Enhancement Techniques
Artificial intelligence, Sparse System Identification, Physics, Harmonics, Computational Mechanics, Voltage, Computer science, Quantum mechanics, Resolution (logic), Engineering, Adaptive Filtering in Non-Gaussian Signal Processing, Computer Science, Physical Sciences, Signal Processing, Computer Vision and Pattern Recognition, Image Denoising Techniques and Algorithms, Sparse Representations, Speech Enhancement Techniques
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