The approach using orthogonal wavelet network (OWN)to tackle this problem is complex.

According to the characteristics of traffic flow,this paper proposes a new model of traffic flow fore- casting based on orthogonal wavelet networks and the forecasting algorithm of comparable time intervals.

Based on the idea of multiresolution hierarchical approximation of wavelet, the identification of nonlinear system with sampled data dispersed irregularly in space is discussed by using orthogonal wavelet networks (OWN).

As the BP neural network is easy to fall into local minimum point and has slow convergence speed, and the RBF neural network has no sole approximation function,the OWNN(Orthogonal Wavelet Neural Network),which takes the Harr orthogonal scaling function as its activation function,is proposed and its weight training algorithm is presented.

The design principle of broadband quadrature networks composed of two RC-all-pass networks is introduced.

Application of Wavelet Network Expert System in fault DiagnoApplication of Wavelet Network Expert System in fault Diagnosis for Generator Set of Ship Power Station;

Application of wavelet network for induction motor in direct torque control system operating at low speed;

Performance measurement for investment decision-making based on wavelet network model;

Application of the wavelet neural network in PD fault diagnosis of electrical power transformers;

A condition detection method for cutting tools based on wavelet neural network(WNN) which collects multi-source feature parameters of cutting tools was proposed to realize on-line state detection based on the non-liner model of WNN.

A model of multiwavelet neural network is proposed according to the multiresolution analysis idea in multiwavelet space in this paper.