Results 111 to 120 of about 8,467,026 (293)
Complexity of Comparing Hidden Markov Models
, 2001 The basic theory of hidden Markov models was developed and applied to problems in speech recognition in the late 1960's, and has since then been applied to numerous problems, e.g. biological sequence analysis. In this paper we consider the problem of computing the most likely string generated by a given model, and its implications on the complexity of ...
Lyngsø, R.B., Pedersen, C.N.S.
openaire +2 more sources
Application of Hidden Markov Models and Hidden Semi-Markov Models to Financial Time Series [PDF]
Hidden Markov Models (HMMs) and Hidden Semi-Markov Models (HSMMs) provide flexible, general-purpose models for univariate and multivariate time series.
Bulla, Jan
core
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
Estimating Components in Finite Mixtures and Hidden Markov Models [PDF]
When the unobservable Markov chain in a hidden Markov model is stationary the marginal distribution of the observations is a finite mixture with the number of terms equal to the number of the states of the Markov chain.
D.S. Poskitt, Jing Zhang
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Multi‐Agent Reinforcement Learning for Joint Police Patrol and Dispatch
Naval Research Logistics (NRL), EarlyView.ABSTRACT Police patrol units need to split their time between performing preventive patrol and being dispatched to serve emergency incidents. In the existing literature, patrol and dispatch decisions are often studied separately. We consider joint optimization of these two decisions to improve police operations efficiency and reduce response time to ...
Matthew Repasky, He Wang, Yao Xie
wiley +1 more source
Improving the performance of Hierarchical Hidden Markov Models on Information Extraction tasks [PDF]
, 2006 This thesis presents novel methods for creating and improving hierarchical hidden Markov models. The work centers around transforming a traditional tree structured hierarchical hidden Markov model (HHMM) into an equivalent model that reuses repeated sub-
Chou, Lin-Yi
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PROTEOMICS, EarlyView.ABSTRACT Cold atmospheric plasma (CAP) is effective against a variety of microorganisms. Here, we described effects on an Escherichia coli strain isolated from hospital wastewater caused by treatment with physical plasma. E. coli GW‐AmxH19 was incubated in artificial wastewater and treated for 15 min with CAP.
Jörg Bernhardt +11 more
wiley +1 more source
Prediction of Prion Proteins in E. coli Based on Bimodal Sequence Characteristics
Proteins: Structure, Function, and Bioinformatics, EarlyView.ABSTRACT Prions are infectious proteins that bear misfolded conformations capable of converting folded states into misfolded aggregates under physiologically relevant conditions. In mammals, prions cause deadly maladies including Creutzfeldt‐Jakob and chronic wasting disease. To date, several prion proteins have been identified in eukaryotes, primarily
Katherine Shreeve +5 more
wiley +1 more source
Feedforward Factorial Hidden Markov Model
MathematicsThis paper introduces a novel kind of factorial hidden Markov model (FHMM), specifically the feedforward FHMM (FFHMM). In contrast to traditional FHMMs, the FFHMM is capable of directly utilizing supplementary information from observations through ...
Zhongxing Peng, Wei Huang, Yinghui Zhu
doaj +1 more source
Detecting Turning Points with Many Predictors through Hidden Markov Models [PDF]
This paper explores the American business cycle with the Hidden Markov Model (HMM) as a monitoring tool using monthly data. It exhibits ten US time series which offer reliable information to detect recessions in real time.
David Saint-Martin, Benoit Bellone
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