An Interval Discrete Wavelet Neural Network Model and Its Numerical Analysis
GUAN Shou-ping, ZHANG Zi-he · 2019
This paper proposes an interval discrete wavelet neural network (IDWNN) model with learning algorithm, which can be used for the system modeling with uncertainty. Compared with the conventional interval BP neural network (IBPNN), IDWNN has both the time-frequency localization characteristics of wavelet analysis and the powerful nonlinear approximation ability, which can provide some guidelines for the network structure construction. The algorithms of the forward calculation and the gradient descent-based back propagation training of IDWNN are derived. The numerical simulation results show the advantages of IDWNN in network structure selection and convergence speed.