An anisotropic and inhomogeneous hidden Markov model for the classification of water quality spatio-temporal series on a national scale: The case of Scotland

2016 ◽  
Vol 28 (1) ◽  
pp. e2427 ◽  
Author(s):  
Luigi Spezia ◽  
Mark J. Brewer ◽  
Christian Birkel
Keyword(s):  
Water Quality ◽  
Markov Model ◽  
Hidden Markov Model ◽  
Hidden Markov ◽  
National Scale ◽  
Temporal Series ◽  
Spatio Temporal

An unsupervised Hidden Markov Model-based system for the detection and classification of blue whale vocalizations off Chile

Bioacoustics ◽  
2019 ◽  
Vol 29 (2) ◽  
pp. 140-167 ◽  
Author(s):  
Susannah J. Buchan ◽  
Rodrigo Mahú ◽  
Jorge Wuth ◽  
Naysa Balcazar-Cabrera ◽  
Laura Gutierrez ◽  
...  
Keyword(s):  
Markov Model ◽  
Hidden Markov Model ◽  
Hidden Markov ◽  
Blue Whale ◽  
Model Based

Classification of Heart Sound Signals Using Autoregressive Model and Hidden Markov Model

2017 ◽  
Vol 7 (4) ◽  
pp. 755-763 ◽  
Author(s):  
Hadrina Sh-Hussain ◽  
M. M. Mohamad ◽  
Raja Zahilah ◽  
Chee-Ming Ting ◽  
Kamarulafizam Ismail ◽  
...  
Keyword(s):  
Markov Model ◽  
Hidden Markov Model ◽  
Autoregressive Model ◽  
Heart Sound ◽  
Hidden Markov

Classification of Encryption Algorithms Using the Hidden Markov Model

2012 ◽  
Vol 64 (3-4) ◽  
pp. 277-290 ◽  
Author(s):  
Prabhat Kumar Ray ◽  
Shri Kant ◽  
Bimal Roy ◽  
Ayanendranath Basu
Keyword(s):  
Markov Model ◽  
Hidden Markov Model ◽  
Hidden Markov ◽  
Encryption Algorithms

scholarly journals A NEURAL-NETWORK-BASED APPROACH TO RECOGNIZING 3D ARM MOVEMENTS

2003 ◽  
Vol 15 (01) ◽  
pp. 17-26 ◽  
Author(s):  
MU-CHUN SU ◽  
YU-XIANG ZHAO ◽  
EUGENE LAI
Keyword(s):  
Neural Network ◽  
Markov Model ◽  
Hidden Markov Model ◽  
Gesture Recognition ◽  
Hidden Markov ◽  
Arm Movements ◽  
Movement Pattern ◽  
Arm Movement ◽  
Hand Gesture ◽  
Spatio Temporal

Gesture recognition is needed for a variety of applications. One particular application of gesture-based systems is to implement a speaking aid for the deaf. Among several factors constituting a hand gesture, the arm movement pattern is one of the most challenging features to recognize. In this paper, we propose a neural-network-based approach to recognition of spatio-temporal patterns of nonlinear 3D arm movements. Compared to Hidden-Markov-Model-based methods, the most appealing property of the proposed method is its simplicity. The effectiveness of this method is evaluated by a database consisted of 10 persons.

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