Results 31 to 40 of about 29,328 (187)

An agent-based implementation of hidden Markov models for gas turbine condition monitoring [PDF]

, 2014
This paper considers the use of a multi-agent system (MAS) incorporating hidden Markov models (HMMs) for the condition monitoring of gas turbine (GT) engines.
Twiddle, John, Catterson, Victoria, Kenyon, Andrew, McArthur, Stephen   +3 more
core   +1 more source

Deep Hidden Semi-Markov Model-Based Speech Synthesis

IEEE Access
This paper proposes a speech synthesis technique based on a neural sequence-to-sequence (Seq2Seq) model that incorporates the structure of hidden semi-Markov models (HSMMs).
Yoshihiko Nankaku, Takato Fujimoto, Takenori Yoshimura, Shinji Takaki, Kei Hashimoto, Keiichiro Oura, Keiichi Tokuda   +6 more
doaj   +1 more source

Vector Autoregressive Hierarchical Hidden Markov Models for Extracting Finger Movements Using Multichannel Surface EMG Signals

Complexity, 2018
We present a novel computational technique intended for the robust and adaptable control of a multifunctional prosthetic hand using multichannel surface electromyography.
Nebojša Malešević, Dimitrije Marković, Gunter Kanitz, Marco Controzzi, Christian Cipriani, Christian Antfolk   +5 more
doaj   +1 more source

Proper account of auto-correlations improves decoding performances of state-space (semi) Markov models

Peer Community Journal
State-space models are widely used in ecology to infer hidden behaviors. This study develops an extensive numerical simulation-estimation experiment to evaluate the state decoding accuracy of four simple state-space models.
Bez, Nicolas, Gloaguen, Pierre, Etienne, Marie-Pierre, Lanco, Sophie, Joo, Rocío, Rivot, Etienne, Walker, Emily, Woillez, Mathieu, Mahévas, Stéphanie   +8 more
doaj   +1 more source

A semi-Markov model for stroke with piecewise-constant hazards in the presence of left, right and interval censoring. [PDF]

, 2013
This paper presents a parametric method of fitting semi-Markov models with piecewise-constant hazards in the presence of left, right and interval censoring. We investigate transition intensities in a three-state illness-death model with no recovery.
Kapetanakis, V, Van Den Hout, Ardo, Kapetanakis, Venediktos, Matthews, FE, Matthews, Fiona E., van den Hout, A   +5 more
core   +1 more source

Efficient Estimation of Time-Dependent Brain Functional Connectivity Using Anatomical Connectivity Constraints

IEEE Access, 2023
There is ongoing interest in the dynamics of resting state brain networks (RSNs) as potential predictors of cognitive and behavioural states. Multivariate Autoregressors (MAR) are used to model regional brain activity as a linear combination of past ...
Hernan Hernandez Larzabal, David Araya, Lazara Liset Gonzalez Rodriguez, Claudio Roman, Nelson Trujillo-Barreto, Pamela Guevara, Wael El-Deredy   +6 more
doaj   +1 more source

Anomalous event detection using a semi-two dimensional hidden Markov model [PDF]

, 2012
The rapid increase in the deployment of CCTV systems has led to a greater demand for algorithms that are able to process incoming video feeds. These algorithms are designed to extract information of interest for human operators.
Nallaivarothayan, Hajananth, Fookes, Clinton B., Hajananth Nallaivarothayan, David Ryan, Denman, Simon, Sridharan, Sridha, Sridha Sridharan, Simon Denman, Ryan, David, Clinton Fookes   +9 more
core   +1 more source

AI‐Assisted Digital Single‐Molecule Activity Tracker for Decoupling Intrinsic Heterogeneity from Photo‐Oxidative Damage in High‐Photon‐Flux Enzymology

Advanced Science, EarlyView.
Employing a digital single‐molecule activity tracker (dSMAT), this research demonstrates that high‐photon‐flux irradiation drives progressive oxidative scarring in polymerases. Unlike simple thermal denaturation, real‐time kinetic tracking dynamically visualizes enzymes degrading into multiple impaired subpopulations.
Anran Zheng, Qi Yang, Jinze Li, Fuqiang Ma, Xuefeng Wang, Zhen Guo, Chuanyu Li, Dongshu Li, Jia Yao, Zhiqi Zhang, Wei Zhang, Lianqun Zhou   +11 more
wiley   +1 more source

HVGH: Unsupervised Segmentation for High-Dimensional Time Series Using Deep Neural Compression and Statistical Generative Model

Frontiers in Robotics and AI, 2019
Humans perceive continuous high-dimensional information by dividing it into meaningful segments, such as words and units of motion. We believe that such unsupervised segmentation is also important for robots to learn topics such as language and motion ...
Masatoshi Nagano, Tomoaki Nakamura, Takayuki Nagai, Takayuki Nagai, Daichi Mochihashi, Ichiro Kobayashi, Wataru Takano   +6 more
doaj   +1 more source

Ovarian Cancer Diagnosis and Chemoresistance Prediction Model Based on cfRNA Molecular Signature

Advanced Science, EarlyView.
A deep learning model analyzes cfRNA profiles extracted from the blood of OVCA patients. This innovative approach distinguishes OVCA from healthy controls with high accuracy. Crucially, it reliably predicts patient response to chemotherapy (sensitive versus resistant subgroups).
Qinhao Guo, Yangyang Zhang, Yongcheng Jin, Siwei Deng, Yongqi Chen, Zheng Feng, Hao Wen, Liu Wang, Yilin Li, Fanghong Ou, Yong Shen, Haiming Li, Tianyao Zhou, Xingzhu Ju, Xiaohua Wu   +14 more
wiley   +1 more source