We propose certified reduced basis methods for the efficient and reliable evaluation of a general output that is implicitly connected to a given parameterized input through the ha...
Yanlai Chen, Jan S. Hesthaven, Yvon Maday, Jer&oac...
A model-constrained adaptive sampling methodology is proposed for reduction of large-scale systems with high-dimensional parametric input spaces. Our model reduction method uses a ...
In this paper, adaptive neural network sliding-mode controller design approach with decoupled method is proposed. The decoupled method provides a simple way to achieve asymptotic ...
Widespread adoption of reconfigurable devices requires system level synthesis techniques to take an application written in a high level language and map it to the reconfigurable d...
This paper presents an efficient method to reduce complexities of a linear network in s-domain. The new method works on circuit matrices directly and reduces the circuit complexi...