TAILIEUCHUNG - Báo cáo hóa học: "Research Article Boosted and Linked Mixtures of HMMs for Brain-Machine Interfaces"

Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: Research Article Boosted and Linked Mixtures of HMMs for Brain-Machine Interfaces | Hindawi Publishing Corporation EURASIP Journal on Advances in Signal Processing Volume 2008 Article ID 216453 12 pages doi 2008 216453 Research Article Boosted and Linked Mixtures of HMMs for Brain-Machine Interfaces Shalom Darmanjian and Jose C. Principe Department of Electrical and Computer Engineering University of Florida Gainesville FL 32611 USA Correspondence should be addressed to Jose C. Principe principe@ Received 9 October 2007 Accepted 26 February 2008 Recommended by Anibal Figueiras-Vidal We propose two algorithms that decompose the joint likelihood of observing multidimensional neural input data into marginal likelihoods. The first algorithm boosted mixtures of hidden Markov chains BMs-HMM applies techniques from boosting to create implicit hierarchic dependencies between these marginal subspaces. The second algorithm linked mixtures of hidden Markov chains LMs-HMM uses a graphical modeling framework to explicitly create the hierarchic dependencies between these marginal subspaces. Our results show that these algorithms are very simple to train and computationally efficient while also reducing the input dimensionality for brain-machine interfaces BMIs . Copyright 2008 S. Darmanjian and J. C. Principe. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited. 1. INTRODUCTION The field of brain-machine interfaces BMIs is devoted to accomplishing the goal of one day restoring paralyzed patients mobility by directly connecting their brain to a machine. A majority of developments in this field have centered around linear and nonlinear models that map neural firing patterns of an animal to a robotic prosthetic 1-3 . Usually in this type of experiment a primate or rat engages in a movement task as neural data is recorded from their cortex as well as the kinematic information . Once a .

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