A Generalization Error Estimate for Nonlinear Systems
نویسنده
چکیده
منابع مشابه
Design of nonlinear parity approach to fault detection and identification based on Takagi-Sugeno fuzzy model and unknown input observer in nonlinear systems
In this study, a novel fault detection scheme is developed for a class of nonlinear system in the presence of sensor noise. A nonlinear Takagi-Sugeno fuzzy model is implemented to create multiple models. While the T-S fuzzy model is used for only the nonlinear distribution matrix of the fault and measurement signals, a larger category of nonlinear systems is considered. Next, a mapping to decou...
متن کاملADAPTIVE FUZZY OUTPUT FEEDBACK TRACKING CONTROL FOR A CLASS OF NONLINEAR TIME-VARYING DELAY SYSTEMS WITH UNKNOWN BACKLASH-LIKE HYSTERESIS
This paper considers the problem of adaptive output feedback tracking control for a class of nonstrict-feedback nonlinear systems with unknown time-varying delays and unknown backlash-like hysteresis. Fuzzy logic systems are used to estimate the unknown nonlinear functions. Based on the Lyapunov–Krasovskii method, the control scheme is constructed by using the backstepping and adaptive techniqu...
متن کاملALGEBRAIC NONLINEARITY IN VOLTERRA-HAMMERSTEIN EQUATIONS
Here a posteriori error estimate for the numerical solution of nonlinear Voltena- Hammerstein equations is given. We present an error upper bound for nonlinear Voltena-Hammastein integral equations, in which the form of nonlinearity is algebraic and develop a posteriori error estimate for the recently proposed method of Brunner for these problems (the implicitly linear collocation method)...
متن کاملRotated Unscented Kalman Filter for Two State Nonlinear Systems
In the several past years, Extended Kalman Filter (EKF) and Unscented Kalman Filter (UKF) havebecame basic algorithm for state-variables and parameters estimation of discrete nonlinear systems.The UKF has consistently outperformed for estimation. Sometimes least estimation error doesn't yieldwith UKF for the most nonlinear systems. In this paper, we use a new approach for a two variablestate no...
متن کاملFast approximation of the bootstrap for model selection
The bootstrap resampling method may be efficiently used to estimate the generalization error of a family of nonlinear regression models, as artificial neural networks. The main difficulty associated with the bootstrap in real-world applications is the high computation load. In this paper we propose a simple procedure based on empirical evidence, to considerably reduce the computation time neede...
متن کامل