Results 61 to 70 of about 2,303,958 (204)

Novel Intersymbol Interference Cancellation Scheme to Enable Parallel Computational and High-Performance Faster-Than-Nyquist Signaling

IEEE Access, 2017
In this paper, we deal with the intersymbol interference (ISI) cancellation problem induced by the faster-than-Nyquist (FTN) signaling. In the traditional FTN signaling, the detection delay at the receiver depends on the number of states of the ISI ...
Bin Qian, Xiaokang Wang, Jinming Wen, Shengli Zhang, Changsheng Chen   +4 more
doaj   +1 more source

Interacting moonlight, weather, and sex influence foraging in a nocturnal insectivore Caprimulgus europaeus

Journal of Avian Biology, Volume 2026, Issue 5, September 2026.
Animals use a variety of environmental cues to identify profitable conditions and increase their foraging efficiency. Identifying environmental correlates of foraging behaviour can help to understand the drivers of animal foraging decisions, and the potential consequences should conditions change.
Lucy J. Mitchell, Piran C. L. White, Kathryn E. Arnold   +2 more
wiley   +1 more source

Genomic adaptation of the water flea Daphnia to elevated temperatures: Insights from power plant‐heated lakes

Limnology and Oceanography, Volume 71, Issue 9, September 2026.
Abstract Global warming increasingly threatens freshwater biodiversity, highlighting the need to understand how key ecological interactors, such as the zooplankton water flea Daphnia, genetically adapt to rising temperatures. Although local thermal adaptation has been documented in Daphnia, the underlying genomic changes remain poorly resolved.
Shaolin Xu, Justyna Wolinska, Marcin Krzysztof Dziuba, Slawek Cerbin, Markus Möst, Luc De Meester   +5 more
wiley   +1 more source

Generating human interactive behaviours using the windowed Viterbi algorithm

In this paper, we propose a new approach for generating interactive behaviours for virtual characters, namely the windowed Viterbi algorithm, capable of doing so in real-time. Consequently, we compare the performance of the standard Viterbi algorithm and
Cosker, Darren P., Marshall, Andrew David, Hicks, Yulia Alexandrovna, Zheng, Y.   +3 more
core   +6 more sources

A Estimation of Stochastic Volatility Models Using Optimized Filtering Algorithms

Austrian Journal of Statistics, 2019
In this paper, we describe and implement two recursive filtering algorithms, the optimized particle filter, and the Viterbi algorithm, which allow the joint estimation of states and parameters of continuous-time stochastic volatility models, such as the ...
Saba Infante, Cesar Luna, Luis Sanchez, Aracelis Hernández   +3 more
doaj   +1 more source

Behavioural state identification from ultra‐high‐frequency movement data

Methods in Ecology and Evolution, Volume 17, Issue 9, Page 2713-2728, September 2026.
Abstract The hidden Markov model (HMM) is a central framework for identifying behavioural state changes from animal movement data. In this context, movement is typically represented as a sequence of observed metrics, such as step length and turning angle distributions, generated by an unobserved behavioural state process.
Abdulmajeed F. Alharbi, Paul G. Blackwell, James Redcliffe, Luca Börger, Jonathan R. Potts   +4 more
wiley   +1 more source

Viterbi algorithm on a hypercube: Concurrent formulation [PDF]

, 1986
The similarity between the Fast Fourier Transform and the Viterbi algorithm is exploited to develop a Concurrent Viterbi Algorithm suitable for a multiprocessor system interconnected as a hypercube.
Pllara, F.
core  

A Novel Entropy-Based Decoding Algorithm for a Generalized High-Order Discrete Hidden Markov Model

Journal of Probability and Statistics, 2018
The optimal state sequence of a generalized High-Order Hidden Markov Model (HHMM) is tracked from a given observational sequence using the classical Viterbi algorithm. This classical algorithm is based on maximum likelihood criterion.
Jason Chin-Tiong Chan, Hong Choon Ong
doaj   +1 more source

Efficient algorithms for training the parameters of hidden Markov models using stochastic expectation maximization (EM) training and Viterbi training

Algorithms for Molecular Biology, 2010
Background Hidden Markov models are widely employed by numerous bioinformatics programs used today. Applications range widely from comparative gene prediction to time-series analyses of micro-array data. The parameters of the underlying models need to be
Meyer Irmtraud M, Lam Tin Y
doaj   +1 more source

A hidden Markov model and reinforcement learning‐based strategy for fault‐tolerant control

The Canadian Journal of Chemical Engineering, Volume 104, Issue 8, Page 4322-4336, August 2026.
Abstract This study introduces a data‐driven control strategy integrating hidden Markov models (HMM) and reinforcement learning (RL) to achieve resilient, fault‐tolerant operation against persistent disturbances in nonlinear chemical processes. Called hidden Markov model and reinforcement learning (HMMRL), this strategy is evaluated in two case studies
Tamera Leitao, Debaprasad Dutta, Simant R. Upreti   +2 more
wiley   +1 more source