Exact(2)
The neural network was used here to obtain a non-parametric model for uncertain systems described by a set of ordinary differential equations.
This article introduces the design of a specific class of non-parametric model for uncertain time-delay system based on CNN considering the so-called delayed learning laws analysis.
Similar(58)
Subsequently, it is problematic to design accurate mathematical models for uncertain systems.
The problem of developing convex function and fuzzy set models for uncertain variables based on limited data and subsequent application in structural safety assessment is considered.
An uncertain Takagi Sugeno (TS) fuzzy model for the uncertain Chen's chaotic system is first constructed.
Interestingly, the average gap and number of branches performed by CRM2, although not directly comparable with the corresponding one of CRM1, results relatively small, confirming the tightness of the class representative model also for uncertain data.
A stochastic analysis model for the uncertain temperature characteristics of expressway embankment is presented.
Takagi and Sugeno fuzzy models with uncertainties are used as the model for the uncertain nonlinear systems.
To facilitate the interpretation of these results, Figure 1 shows the predicted probability (from the cumulative logistic model) for making "uncertain", "weak", or "strong" recommendation (for or against the intervention) as a function of quality.
In the control theoretic framework, a new power and rate control system model is derived for uncertain wireless networks with time-varying delays in both state and control input.
A newly developed robust Model Predictive Control method for uncertain and output constrained dynamic systems is a key control technology employed at Optimising Control Level.
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