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> Yoshitaka Ito
(Last updated : 2023-11-19 15:44:33)
Yoshitaka Ito
Department / Course
Hokkaido University of Science Faculty of Engineering Department of Electrical and Electronic Engineering
Job
Associate Professor
Achievement
Academic background
Present specialized field
Belonging society
Book and thesis
Academic conference presentation
Academic background
2019/03/18
Degree Acquisition
2011/03
Degree Acquisition
Present specialized field
Others, Others
Belonging society
2022/08 ~
The Institute of Electrical Engineers of Japan
Book and thesis
Papers
A Method for Quantifying the Complexity of Graph Structure Obtained from Chaotic Time Series Data (Co-authored) 2023/09/26
Papers
Predicting a Critical Transition in a Five-Dimensional Ecosystem Using Parameter Space (Sole-authored) 2023/09/26
Papers
Predicting the parameter value at which a critical transition occurs from the Lyapunov exponents in an estimated parameter space Nonlinear Theory and Its Applications (Sole-authored) 2023/07/01
Papers
Verifying the robustness of using parameter space estimation with ridge regression to predict a critical transition Nonlinear Theory and Its Applications (Sole-authored) 2023/07/01
Papers
Detecting Unstable Sets in an Estimated Parameter Space for the Henon Map, Journal of Applied Nonlinear Dynamics Journal of Applied Nonlinear Dynamics (Sole-authored) 2023/04/01
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Academic conference presentation
2021/10/26
Modeling of Quantum Electron Transmission Process in Two-dimensional Nanowire System using Recurrent Neural Network, MNC2021, remote, 2021. (34th International Microprocesses and Nanotechnology Conference)
2021/03
Relationship between Success Rate of Bifurcation Diagrams Reconstruction and Synaptic Weight Vectors of Predictor (RISP International Workshop on Nonlinear Circuits, Communications and Signal Processing 2021)
2020/11
Reconstructing bifurcation diagrams of all components in Rossler equations only from time-series data sets (2020 International Symposium on Nonlinear Theory and its Applications)
2020/03
Effects of Omitting Pruning Procedure on Extreme Learning Machine for Bifurcation Diagrams (RISP International Workshop on Nonlinear Circuits, Communications and Signal Processing 2020)
2018/11
Reconstructing Bifurcation Diagrams of a Chaotic Neuron Model Using an Extremely Learning Machine (The 9th International Conference on Extreme Learning Machines)
Display All(12)