Researcher Database | Faculty of Engineering Department of Electrical and Electronic Engineering | Yoshitaka Ito |

（Last updated : 2025-06-09 15:56:33）

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Yoshitaka Ito

Department / Course Hokkaido University of Science Faculty of Engineering Department of Electrical and Electronic Engineering

Job Associate Professor

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	Predicting critical transitions induced by the saddle-node bifurcation in electronic circuits using parameter space estimation (Sole-authored) 2025/03/15
Papers	Investigating the Correspondence Between Original Parameter Space and Synaptic Weight Space for Parameter Space Estimation (Sole-authored) 2025/03/02
Papers	Stability analysis method using extreme learning machine trained on time-series data and parameters in autonomous systems (Co-authored) 2024/12/13
Papers	Parameter Space Estimation for The Tent Map Using a Neural Network with Gate Neurons (Sole-authored) 2024/12/06
Papers	Variational Autoencoder Approach to Designing Nanowire Impurity Distributions with Targeted Electron Transmittance Characteristics (Co-authored) 2024/11/12
Display All（19）

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）