2 citations · 2 across the 6 of their papers we have counts for
7 papers
Input-to-State Stability Implications in Contraction Theory
Yu Kawano, Francesco Bullo
For nonlinear control systems on normed vector spaces, we characterize an incremental input-to-state stability (ISS) type property in which the overshoot constant multiplies both t…
Contraction Analysis of Time-Delay Systems
Rintaro Watanabe, Yu Kawano
In this paper, we investigate contraction analysis for nonlinear time-delay systems described by functional differential equations. We first extend the concept of Lyapunov-Krasovsk…
A Nonlinear Separation Principle via Contraction Theory: Applications to Neural Networks, Control, and Learning
Anand Gokhale, Anton V. Proskurnikov, Yu Kawano +1
This paper establishes a nonlinear separation principle based on contraction theory and derives sharp stability conditions for recurrent neural networks (RNNs). First, we introduce…
Contracting Neural Networks: Sharp LMI Conditions with Applications to Integral Control and Deep Learning
Anand Gokhale, Anton V. Proskurnikov, Yu Kawano +1
This paper studies contractivity of firing-rate and Hopfield recurrent neural networks. We derive sharp LMI conditions on the synaptic matrices that characterize contractivity of b…
Krasovskii Passivity for Sampled-data Stabilization and Output Consensus
Yu Kawano, Alessio Moreschini, Michele Cucuzzella
In this paper, we establish the novel concept of Krasovskii passivity for sampled discrete-time nonlinear systems, enabling Krasovskii-passivity-based control design under sampling…
An LMI Framework for Contraction-based Nonlinear Control Design by Derivatives of Gaussian Process Regression
Yu Kawano, Kenji Kashima
Contraction theory formulates the analysis of nonlinear systems in terms of Jacobian matrices. Although this provides the potential to develop a linear matrix inequality (LMI) fram…
Contraction Analysis of Discrete-time Stochastic Systems
Yu Kawano, Yohei Hosoe
In this paper, we develop a novel contraction framework for stability analysis of discrete-time nonlinear systems with parameters following stochastic processes. For general stocha…