Real-time performance evaluation of the minimal radial basis function network for identification of time varying nonlinear systems

Computers and Electrical Engineering

Volumn 28, Issue 2, 2002, Pages 103-117

  Leong, T K ^a   Saratchandran, P ^a   Sundararajan, N ^a  

^a NANYANG TECHNOLOGICAL UNIVERSITY   (Singapore)

Author keywords

Nonlinear system; RBF network; Real time; Time varying signal identification

Indexed keywords

ALGORITHMS; COMPUTATION THEORY; NONLINEAR SYSTEMS; REAL TIME SYSTEMS; RESOURCE ALLOCATION; SAMPLING; TIME VARYING SYSTEMS;

MINIMAL RESOURCE ALLOCATION NETWORKS (MRAN);

RADIAL BASIS FUNCTION NETWORKS;

EID: 0036497449     PISSN: 00457906     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0045-7906(00)00039-2     Document Type: Article

References (9)

1. Neural networks for nonlinear dynamic system modelling and identification
2. A closer look at radial basic function (RBF) networks
3. A sequential learning scheme for function approximation by using minimal radial basic function neural networks
4. Identification of time-varying nonlinear systems using minimal radial basic function neural network learning algorithm
5. A resource allocating network for function interpolation
6. A function estimation approach to sequential learning with neural networks
7. Recursive hybrid algorithm for nonlinear system identification using radial basic function networks
8. On-line identification of nonlinear time varying systems using structurally adaptive radial basic function networks
9. Off-line identification of nonlinear system using structurally adaptive radial basic function networks