Signal classification has many important applications in both of the civilian and military domains. This paper presents a classification of multi-user chirp modulation signals using wavelet higher order statistics features and neural network classifier (NN). In this paper, even higher order moments and cumulants up to order eight from the discrete wavelet transform (DWT) coefficients are propos...

In this paper, an automatic system is presented for word recognition using real Turkish word signals. This paper especially deals with combination of the feature extraction and classification from real Turkish word signals. A Discrete Wavelet Neural Network (DWNN) model is used, which consists of two layers: discrete wavelet layer and multi-layer perceptron. The discrete wavelet layer is used f...

We introduce a two-layer wavelet scattering network, for object classification. This scattering transform computes a spatial wavelet transform on the first layer and a new joint wavelet transform along spatial, angular and scale variables in the second layer. Numerical experiments demonstrate that this two layer convolution network, which involves no learning and no max pooling, performs effici...

An application of Beta wavelet networks to synthesize pass-high and pass-low wavelet filters is investigated in this work. A Beta wavelet network is constructed using a parametric function called Beta function in order to resolve some nonlinear approximation problem. We combine the filter design theory with wavelet network approximation to synthesize perfect filter reconstruction. The order fil...

Short term traffic forecasting has been a very important consideration in many areas of transportation research for more than 3 decades. Short-term traffic forecasting based on data driven methods is one of the most dynamic and developing research arenas with enormous published literature. In order to improve forecasting model accuracy of wavelet neural network, an adaptive particle swarm optim...