A New Coupled-HMM Framework with Applications in Multichannel Brain Signal Processing, Ph.D. Dissertation Sharif University of Technology ; Shamsollahi, Mohammad Bagher (Supervisor)
Abstract
The human brain can be described as a dynamic system with multiple subsystems interacting with one another and multi-channel observations of these subsystems are available. The modeling of a system from its observations allows us to gain insight into how its various components interact with one another and also provides intuition about the desired system. Hidden Markov Model (HMM) is a probabilistic model with hidden states that is suitable for modeling these types of systems. Multi-channel observations are available from several subsystems interacting with each other within a general system. In this case, it may be necessary to develop more comprehensive models incorporating multi-channel...
Cataloging briefA New Coupled-HMM Framework with Applications in Multichannel Brain Signal Processing, Ph.D. Dissertation Sharif University of Technology ; Shamsollahi, Mohammad Bagher (Supervisor)
Abstract
The human brain can be described as a dynamic system with multiple subsystems interacting with one another and multi-channel observations of these subsystems are available. The modeling of a system from its observations allows us to gain insight into how its various components interact with one another and also provides intuition about the desired system. Hidden Markov Model (HMM) is a probabilistic model with hidden states that is suitable for modeling these types of systems. Multi-channel observations are available from several subsystems interacting with each other within a general system. In this case, it may be necessary to develop more comprehensive models incorporating multi-channel...
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