Recursive least-squares (RLS) algorithms are widely used in many applications, such as real-time signal processing, control and communications. In some regularization of the provides robustness enhances performance. Interestingly, updating parameter processing data continuously time is a desirable strategy to improve performance applications beamforming. While presented works literature assume ...

this paper investigates the forecasting performance of different time-varying bvar models for iranian inflation. forecast accuracy of a bvar model with litterman’s prior compared with a time-varying bvar model (a version introduced by doan et al., 1984); and a modified time-varying bvar model, where the autoregressive coefficients are held constant and only the deterministic components are allo...

A continuous adaptive controller is developed for nonlinear dynamical systems with linearly parameterizable uncertainty involving time-varying uncertain parameters. Through a unique stability analysis strategy, new feedforward term along specialized feedback terms, to yield an asymptotic tracking error convergence result by compensating the nature of Lyapunov-based shown Euler–Lagrange systems,...

| A novel observer for tracking and identifying a chaotic system with time-varying bifurcation parameters via an observation signal contaminated by additive white Gaussian noise (AWGN) is developed in this paper. It is realized by an adaptive algorithm which takes advantage of the good approximation capability of the Radial Basis Function (RBF) neural network and the ability of the Extended Kal...