As a general and rigid mathematical tool, wavelet theory has found many applications and is
constantly developing. This article reviews the development history of wavelet theory, from …

Wavelet networks are a class of neural networks consisting of wavelets. In this paper,
algorithms for wavelet network construction are proposed for the purpose of nonparametric …

Wavelet networks (WNs) are a new class of networks which have been used with great
success in a wide range of applications. However a general accepted framework for …

In a world of almost permanent and rapidly increasing electronic data availability,
techniques of filtering, compressing, and interpreting this data to transform it into valuable …

As modern vehicles system becomes increasingly complex, there is an urgent need to
develop a framework to monitor the behavior and detect the unhealthy states to …

Pati and Krishnaprasad (1990) first studied the connection between neural networks and
wavelet transforms. Zhang and Benveniste (1992) gave a different treatment of this …

With the development of information technology, image has become the mainstream of
information transmission. Compared with character, image contains more information, but …

The minimal model structure detection (MMSD) problem in nonlinear dynamic system
identification is formulated as a search for the optimal orthogonalization path. While an …

Stable neural network control and estimation may be viewed formally as a merging of
concepts from nonlinear dynamic systems theory with tools from multivariate approximation …

This paper presents a wavelet neural network (WNN) based method to reduce reliance on
wearable kinematic sensors in gait analysis. Wearable kinematic sensors hinder real-time …