In this paper, we establish the more robust notion of approximate bisimulation equivalence for nondeterministic nonlinear systems. This is achieved by requiring ...
Dec 14, 2017 · Bibliographic details on Optimal structure analysis of universal learning network with multi-branches.
In this paper, multi-branch structures of ULNs are studied to evaluate their potential for approximating functions and modeling dynamical systems with good ...
Missing: Optimal analysis
Optimal identification method of nonlinear system based on GA-GHNNs P ... Gaussian-Hopfield neural network algorithm (GHNNs) is the most commonly used method of ...
Min Han, Xiaomeng Jia, Kotaro Hirasawa: Affection of the multi-branch number of universal learning networks on network structure. SMC 2001: 610-615; 2000.
The structure of Universal Learning Network with the multi-branches and filtering structures is shown in Figure ... "optimal" means that both the modeling error ...
Jun 9, 2020 · In this work, we present an automated multi-task learning algorithm that learns where to share or branch within a network, designing an ...
Missing: analysis | Show results with:analysis
Abstract: Universal Learning Network(U.L.N.), which can model and control the large scale complicated systems naturally, consists of nonlinearly operated ...
In this paper, a method to construct the fuzzy model with a multi-dimension input membership function using ULN is presented. ... Assuming the time delays to be.