Results 61 to 70 of about 62,966 (184)
Human activity learning and segmentation using partially hidden discriminative models [PDF]
, 2005 Learning and understanding the typical patterns in the daily activities and routines of people from low-level sensory data is an important problem in many application domains such as building smart environments, or providing intelligent assistance ...
Bui, Hung H. +2 more
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hsmm — An R package for analyzing hidden semi-Markov models
Computational Statistics & Data Analysis, 2010 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Bulla, Jan, Bulla, Ingo, Nenadic, Oleg
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Explicit Modeling of Brain State Duration Using Hidden Semi Markov Models in EEG Data
IEEE AccessWe consider the detection and characterization of brain state transitions based on ongoing electroencephalography (EEG). Here, a brain state represents a specific brain dynamical regime or mode of operation that produces a characteristic quasi-stable ...
Nelson J. Trujillo-Barreto +3 more
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Design of Abnormal Heart Sound Recognition System Based on HSMM and Deep Neural Network
Medical Devices: Evidence and Research, 2022 Hai Yin,1 Qiliang Ma,2 Junwei Zhuang,1 Wei Yu,1 Zhongyou Wang3 1School of Biomedical Engineering and Medical Imaging, Xianning Medical College, Hubei University of Science and Technology, Xianning, 437100, People’s Republic of China; 2School of ...
Yin H, Ma Q, Zhuang J, Yu W, Wang Z
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International Journal of Distributed Sensor Networks, 2013 Most of analyses for the IEEE 802.15.4 Carrier Sense Multiple Access with Collision Avoidance (CSMA/CA) scheme for multi-hop wireless sensor networks (WSNs) focus on how to avoid the impacts of hidden terminal problems rather than how to derive the exact
Jianping Zhu, Chunfeng Lv, Zhengsu Tao
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Neuron's eye view: Inferring features of complex stimuli from neural responses. [PDF]
PLoS Computational Biology, 2017 Experiments that study neural encoding of stimuli at the level of individual neurons typically choose a small set of features present in the world-contrast and luminance for vision, pitch and intensity for sound-and assemble a stimulus set that ...
Xin Chen, Jeffrey M Beck, John M Pearson
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A hidden semi-Markov model for estimating burst suppression EEG [PDF]
2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2019 Burst suppression is an electroencephalogram (EEG) pattern associated with profoundly inactivated brain states characterized by cerebral metabolic depression. This pattern is distinguished by short-duration band-limited electrical activity (bursts) interspersed between relatively near-isoelectric periods (suppressions).
Chakravarty, Sourish +4 more
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Route Restoring Based on Hidden Semi-Markov Model
Advances in Intelligent Systems Research, 2014 Present raw geo-tagged photo routes cannot provide information as enough as complete GPS trajectories due to the defects hidden in them. This paper mainly aims at analyzing the large amounts of geo-tagged photos and proposing a novel travel route restoring method. In our approach we apply the Hidden SemiMarkov model and Mean Value method to demonstrate
Zhenmin Zhu, Jian Ye, Guannan Wang
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Decoding Chinese stock market returns: Three-state hidden semi-Markov model [PDF]
Pacific-Basin Finance Journal, 2017 In this paper, we employ a three-state hidden semi-Markov model (HSMM) to explain the time-varying distribution of the Chinese stock market returns since 2005. Our results indicate that the time-varying distribution depends on the hidden states, which are represented by three market conditions, namely the bear, sidewalk, and bull markets.
Liu, Zhenya, Wang, Shixuan
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Hierarchical semi-markov conditional random fields for recursive sequential data [PDF]
, 2008 Inspired by the hierarchical hidden Markov models (HHMM), we present the hierarchical semi-Markov conditional random field (HSCRF), a generalisation of embedded undirected Markov chains to model complex hierarchical, nested Markov processes.
Bui, Hung H. +3 more
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