Search Results - "Nonlinear Theory and Its Applications IEICE" :: K.UTB vyhledávací portál

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Reconstructive reservoir computing for anomaly detection in time-series signals

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Theoretical analysis of the three-dimensional CAC considering connection and communication quality

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Erratum: Reservoir computing-based mental simulation for direct action sequence optimization [Nonlinear Theory and Its Applications, IEICE Vol.15 (2024) , No.2 pp.421-431]

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Effective learning algorithm for restricted Boltzmann machines via spatial Monte Carlo integration

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Robot formation control in nonlinear manifold using Koopman operator theory

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Quasi-free energy evaluation of Gaussian-Bernoulli restricted Boltzmann machine for anomaly detection

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Design and evaluation of brain-inspired predictive coding networks based on the free-energy principle for novel neuromorphic hardware

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Effective sampling on Gaussian-Bernoulli restricted Boltzmann machines

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Review of the analytical prediction method of surf-riding threshold in following sea, and its relation to IMO Second-Generation Intact Stability Criteria

Published in Nonlinear Theory and Its Applications IEICE (01.01.2024)

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Q-learning-based distributed multi-charging algorithm for large-scale WRSNs

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Traffic matrix completion by weighted tensor nuclear norm minimization and time slicing

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Investigation of the structure of the latent variable space in Sentence-BERT sentence vectors using an image generation model

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A UAV traffic prediction considering AP connection errors and UAV altitude

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Evaluation of an effective solving method based on cooperative multi-objective differential evolution for multi-objective optimization problems

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Automation and acceleration of graph cut based image segmentation utilizing U-net

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Simultaneously estimating and controlling nonlinear neuronal dynamics based on sequential Monte Carlo framework

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High-order polynomial activation function and regenerative internal weights for FPGA implementation of reservoir computing

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Hierarchical lossless color image coding method using cellular neural networks based predictors

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Introduction to the FDTD method and its application to implicit locally one-dimensional calculations

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Fast convergence to an approximate solution by message-passing for complex optimizations

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