Results 41 to 50 of about 29,328 (187)
Feature Selection for Hidden Markov Models and Hidden Semi-Markov Models
IEEE Access, 2016 In this paper, a joint feature selection and parameter estimation algorithm is presented for hidden Markov models (HMMs) and hidden semi-Markov models (HSMMs).
Stephen Adams +2 more
doaj +1 more source
First-Order Uncertain Hidden Semi-Markov Process for Failure Prognostics With Scarce Data
IEEE Access, 2020 Failure prognostics aims at predicting the object equipment's future degradation trend and derives the remaining useful life with a predefined failure threshold.
Jie Liu
doaj +1 more source
Biological Reviews, EarlyView.ABSTRACT Recent methodological development in phylogenetic inference has focused predominantly on molecular data. However, renewed interest in other data types, particularly morphological data, has followed from the increased recognition of the power of total evidence and tip‐dating approaches, including fossil data, for inference of time‐scaled trees ...
Melanie J. Hopkins +9 more
wiley +1 more source
Option pricing using hidden Markov models [PDF]
, 2006 Includes bibliographical references (leaves 144-149).This work will present an option pricing model that accommodates parameters that vary over time, whilst still retaining a closed-form expression for option prices: the Hidden Markov Option Pricing ...
Anderson, Michael
core
Stochastic Gradient Descent in High Dimensions for Multi‐Spiked Tensor PCA
Communications on Pure and Applied Mathematics, EarlyView.ABSTRACT We study the high‐dimensional dynamics of online stochastic gradient descent (SGD) for the multi‐spiked tensor model. This multi‐index model arises from the tensor principal component analysis (PCA) problem with multiple spikes, where the goal is to estimate the unknown signal vectors within the N$N$‐dimensional unit sphere through maximum ...
Gérard Ben Arous +2 more
wiley +1 more source
iMetaOmics, EarlyView.An integrative metagenomic framework combining sequence, structural, and functional inference reveals a phylogenetically diverse and structurally conserved repertoire of putative beta‐lactamases across Antarctic soil microbiomes, with predominance of class A and subclass B3 enzymes and limited but detectable associations with mobile genetic elements ...
José Coche‐Miranda +8 more
wiley +1 more source
Sensors, 2019 Lower limb locomotion activity is of great interest in the field of human activity recognition. In this work, a triplet semi-Markov model-based method is proposed to recognize the locomotion activities of healthy individuals when lower limbs move ...
Haoyu Li +2 more
doaj +1 more source
Kajian Model Hidden Markov untuk Menduga Volatilitas Indeks Harga Saham [PDF]
, 2013 Volatility is a measure of uncertainty, which is useful for investor to plan a good investment strategy. The problem is that volatility is unobservable, and estimating volatility is not a trivial task.
Baist, Abdul
core
Figure 4. A chromosome structure for HMM shown in Figure 2.-Neuroevolution Mechanism for Hidden Markov Model [PDF]
, 2011 The chromosome which represents the HMM can be extracted from its corresponding neural network. The general structure of the chromosome is divided into two sections, input layer and hidden layer. Each section contains many slots, and each slot represents
Neuroevolution Mechanism for Hidden Markov Model (5584958) +1 more
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Mathematical Methods in the Applied Sciences, EarlyView.We develop a full randomization of the classical hyper‐logistic growth model by obtaining closed‐form expressions for relevant quantities of interest, such as the first probability density function of its solution, the time until a given fixed population is reached, and the population at the inflection point.
Juan Carlos Cortés +2 more
wiley +1 more source