Results 81 to 90 of about 241,122 (289)
Hidden Markov graphical models with state‐dependent generalized hyperbolic distributions
Canadian Journal of Statistics, EarlyView.Abstract In this article, we develop a novel hidden Markov graphical model to investigate time‐varying interconnectedness between different financial markets. To identify conditional correlation structures under varying market conditions and accommodate shape features embedded in financial time series, we rely upon the generalized hyperbolic family of ...
Beatrice Foroni +2 more
wiley +1 more source
Forecasting New Cases of Bipolar Disorder Using Poisson Hidden Markov Model
International Clinical Neuroscience Journal, 2018 Background: Bipolar disorder (BD) is a major public health problem. In time series count data there may be over dispersion, and serial dependency. In such situation some models that can consider the dependency are needed. The purpose current research was
Behnaz Alafchi +4 more
doaj +1 more source
Local Equivalence Problem in Hidden Markov Model
, 2019 In the hidden Markov process, there is a possibility that two different transition matrices for hidden and observed variables yield the same stochastic behavior for the observed variables.
Hayashi, Masahito
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Twenty years of dynamic occupancy models: a review of applications and look to the future
Ecography, EarlyView.Since their introduction over 20 years ago, dynamic occupancy models (DOMs) have become a powerful and flexible framework for estimating species occupancy across space and time while accounting for imperfect detection. As their popularity has increased and extensions have further expanded their capabilities, DOMs have been applied to increasingly ...
Saoirse Kelleher +3 more
wiley +1 more source
Applied Computer ScienceThe best emotion recognition system based on physiological signals with a simple operatory should have higher accuracy and fast response speed. This paper aims to develop an emotion recognition system using a novel hybrid system based on Hidden Markov ...
Sahar ZAMANI KHANGHAH, Keivan MAGHOOLI
doaj +1 more source
Energy Science &Engineering, EarlyView.Schematic diagram showing the proposed approach for EV charging/discharging. ABSTRACT The number of electric vehicles (EVs) on the road is rising as a result of recent advancements in EV technology, and EVs are important to the smart grid economy. Demand response schemes involving electric vehicles have the potential to dramatically reduce the cost of ...
F. Zonuntluanga +6 more
wiley +1 more source
EntropyWe define an evolving in-time Bayesian neural network called a Hidden Markov Neural Network, which addresses the crucial challenge in time-series forecasting and continual learning: striking a balance between adapting to new data and appropriately ...
Lorenzo Rimella, Nick Whiteley
doaj +1 more source
Journal of Electrical Systems and Information Technology, 2017 This paper presents an analytical approach of an offline handwritten Arabic text recognition system. It is based on the Hidden Markov Models (HMM) Toolkit (HTK) without explicit segmentation. The first phase is preprocessing, where the data is introduced
El Moubtahij Hicham +2 more
doaj +1 more source
Energy Science &Engineering, EarlyView.A deep reinforcement learning–based control architecture is proposed to coordinate heat pumps, thermal storage, renewable energy, and demand response in data center waste heat recovery systems. The agent learns optimal control actions from system states and reward feedback to achieve electrical–thermal co‐optimization under realistic operational ...
Rendong Shen +5 more
wiley +1 more source
Experiments on the Application of IOHMMs to Model Financial Returns Series [PDF]
Input/Output Hidden Markov Models (IOHMMs) are conditional hidden Markov models in which the emission (and possibly the transition) probabilities can be conditioned on an input sequence.
Réjean Ducharme +2 more
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