Brain Decoding Across Subjects, M.Sc. Thesis Sharif University of Technology ; Shamsollahi, Mohammad Bagher (Supervisor)
Abstract
In recent years, techniques in articial intelligence have become an important tool in the analysis of physiological signals. While the application of machine learning techniques has proved useful in other elds, researchers have had difficulty proving its utility for the analysis of physiological signals. A major challenge in applying such techniques to the analysis of physiological signals is dealing effectively with inter-patient differences. The morphology and interpretation of physiological signals can vary dep ending on the patient. This poses a problem, since statistical learning techniques aim to estimate the underlying system that produced the data. If the system (or patient) changes...
Cataloging briefBrain Decoding Across Subjects, M.Sc. Thesis Sharif University of Technology ; Shamsollahi, Mohammad Bagher (Supervisor)
Abstract
In recent years, techniques in articial intelligence have become an important tool in the analysis of physiological signals. While the application of machine learning techniques has proved useful in other elds, researchers have had difficulty proving its utility for the analysis of physiological signals. A major challenge in applying such techniques to the analysis of physiological signals is dealing effectively with inter-patient differences. The morphology and interpretation of physiological signals can vary dep ending on the patient. This poses a problem, since statistical learning techniques aim to estimate the underlying system that produced the data. If the system (or patient) changes...
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