In this paper, a recursive nonlinear filter exploiting trigonometric expansions of the past output samples is introduced. Its peculiarity is, in general, the ability to model rea...
The paper discusses computationally efficient NLMS and RLS algorithms for a broad class of nonlinear filters using periodic input sequences. The class comprises all nonlinear ...
Alberto Carini, V. John Mathews, Giovanni L. Sicur...
Abstract--In this paper, we introduce a novel approach for improved nonlinear system identification in the short-time Fourier transform (STFT) domain. We first derive explicit repr...
— Consider a scenario in which the data owner has some private/sensitive data and wants a data miner to access it for studying important patterns without revealing the sensitive ...
Kanishka Bhaduri, Mark D. Stefanski, Ashok N. Sriv...
The classical inexact Newton algorithm is an efficient and popular technique for solving large sparse nonlinear system of equations. When the nonlinearities in the system are wellb...
Abstract An extension of the Gauss-Newton algorithm is proposed to find local minimizers of penalized nonlinear least squares problems, under generalized Lipschitz assumptions. Co...
Abstract-- This paper focuses on the identification of nonlinear hybrid systems involving unknown nonlinear dynamics. The proposed method extends the framework of [1] by introducin...
In this paper, network-based cooperative control of nonlinear dynamical systems is investigated. A theorem on cooperative stability is presented for designing nonlinear consensus a...
Accurately simulating neurons with realistic morphological structure and synaptic inputs requires the solution of large systems of nonlinear ordinary differential equations. We ap...
Anthony R. Kellems, Saifon Chaturantabut, Danny C....