Solution to error source model selection problem in IS EASECC
Advanced Engineering Research, 2017 Introduction. The development of error-correcting techniques in digital transmission channels is considered. This is a multiparameter problem the solution of which through the analytical methods is rather difficult.
Vladimir M Deundyak +2 more
doaj +1 more source
Generalizing Robot Imitation Learning with Invariant Hidden Semi-Markov Models
, 2018 Generalizing manipulation skills to new situations requires extracting invariant patterns from demonstrations. For example, the robot needs to understand the demonstrations at a higher level while being invariant to the appearance of the objects ...
Calinon, Sylvain +7 more
core
Prediction and Power in Molecular Sensors: Uncertainty and Dissipation When Conditionally Markovian Channels Are Driven by Semi-Markov Environments [PDF]
, 2017 Sensors often serve at least two purposes: predicting their input and minimizing dissipated heat. However, determining whether or not a particular sensor is evolved or designed to be accurate and efficient is difficult.
Crutchfield, James P., Marzen, Sarah E.
core +1 more source
SynSys: A Synthetic Data Generation System for Healthcare Applications
Sensors, 2019 Creation of realistic synthetic behavior-based sensor data is an important aspect of testing machine learning techniques for healthcare applications. Many of the existing approaches for generating synthetic data are often limited in terms of complexity ...
Jessamyn Dahmen, Diane Cook
doaj +1 more source
Interleaved Factorial Non-Homogeneous Hidden Markov Models for Energy Disaggregation [PDF]
, 2014 To reduce energy demand in households it is useful to know which electrical appliances are in use at what times. Monitoring individual appliances is costly and intrusive, whereas data on overall household electricity use is more easily obtained.
Goddard, Nigel +2 more
core
Inference in Hidden Markov Models with Explicit State Duration Distributions
, 2012 In this letter we borrow from the inference techniques developed for unbounded state-cardinality (nonparametric) variants of the HMM and use them to develop a tuning-parameter free, black-box inference procedure for Explicit-state-duration hidden Markov ...
Dewar, Michael +2 more
core +2 more sources
Convergence properties of dynamic mode decomposition for analytic interval maps
Communications on Pure and Applied Mathematics, Volume 79, Issue 2, Page 179-206, February 2026.Abstract Extended dynamic mode decomposition (EDMD) is a data‐driven algorithm for approximating spectral data of the Koopman operator associated to a dynamical system, combining a Galerkin method with N$N$ functions and a quadrature method with M$M$ quadrature nodes.
Elliz Akindji +3 more
wiley +1 more source
Hybrid Parallel Model of Semi-Blind Joint Timing-Offset and Channel Estimation for AF-TWRNs
IEEE AccessTiming offset and channel estimation plays an important role in the performance of amplify-and-forward two-way relay networks. The state-of-the art approach models the system as a Hidden Markov Model (HMM) and performs semi-blind estimation using ...
Ali A. El-Moursy +5 more
doaj +1 more source
The Journal of Wildlife Management, Volume 90, Issue 2, February 2026.We investigated low American oystercatcher (Haematopus palliatus) productivity in the Virginia barrier islands, which historically supported high oystercatcher reproductive success. We found that chick survival was lower than nest survival, and that management may need to adapt to address evolving threats from coastal flooding and a multi‐guild ...
Mikayla N. Call +6 more
wiley +1 more source
Opportunistic Channel Access Algorithm Based on Hidden Semi Markov Model for Cognitive Radio Networks [PDF]
, 2014 Bhupal Kumar, Dr.S.K. Srivatsa
openalex +1 more source