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Study Topics
We explore analysis and synthesis of dynamical systems from broad perspective using mathematical systems theory. Currently, we are actively working on the reliability/stability verification of AI systems on the basis of optimization and control theory.Special Events
News
December 2024: New Research Project Launched New!!Japan Science and Technology Agency (JST)
Adopting Sustainable Partnerships for Innovative Research Ecosystem (ASPIRE)
"Building Mathematical Foundation for Cyber Physical Dynamical Systems: Interdisciplinary Research and Human Resource Development on Control with Prediction and Learning"
PI: Y. Ebihara
Press Release can be found here.

The following paper that deals with the verification of NN-driven control systems have been accepted for publication at Transactions of the Society of Instrument and Control Engineers,
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T. Yuno, K. Fukuchi, and Y. Ebihara,
Construction and Input-to-Output Characteristics Evaluation of Compressed Model of Recurrent Neural Networks for their Stability Analysis (in Japanese)

The following papers that deal with the verification of NN-driven control systems have been accepted for presentation at IEEE Conference on Decision and Control 2024.
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T. Yuno, K. Fukuchi, and Y. Ebihara,
A Lyapunov-based Method of Reducing Activation Functions of Recurrent Neural Networks for Stability Analysis
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T. Yuno, S. Nishinaka, R. Saeki, and Y. Ebihara,
On Static O'Shea-Zames-Falb Multipliers for Idempotent Nonlinearities
