This research determined the potential for wavelet-based analysis of hyperspectral reflectance signals for detecting the presence of early season pitted morningglory when intermixed with soybean and soil. Ground-level hyperspectral reflectance signals were collected in a field experiment containing plots of soybean and plots containing soybean intermixed with pitted morningglory in a convention...

abstract obligatory modelling of precipitations in various periods, have a lot of problems and weakness because of their casual nature in time and space. moreover, their uncertainty in predictions, reduce credibility of estimations which have done via these models. wavelet is one of the novel and very effective methods in analyzing of time series and signals considered in the hydrology in recen...

Target threat assessment is a key issue in the collaborative attack. To improve the accuracy and usefulness of target threat assessment in the aerial combat, we propose a variant of wavelet neural networks, MWFWNN network, to solve threat assessment. How to select the appropriate wavelet function is difficult when constructing wavelet neural network. This paper proposes a wavelet mother functio...

Abstract: In this paper, a predictive control method using self-recurrent wavelet neural network (SRWNN) is proposed for chaotic systems. Since the SRWNN has a self-recurrent mother wavelet layer, it can well attract the complex nonlinear system though the SRWNN has less mother wavelet nodes than the wavelet neural network (WNN). Thus, the SRWNN is used as a model predictor for predicting the d...

Accurate groundwater level modeling and forecasting contribute to civil projects, land use, citys planning and water resources management. Combined Wavelet-Artificial Neural Network (WANN) model has been widely used in recent years to forecast hydrological and hydrogeological phenomena. This study investigates the sensitivity of the pre-processing to the wavelet type and decomposition level in ...

The process of calculating the effective values of voltage and current root mean square (RMS) using Fourier transform (FT) suffers a high computational effort. Since it provides only an amplitude-frequency spectrum, looses time-related information, and is unable to deal with no stationary waveforms, standard definitions are reformulated in the time-frequency domain using the wavelet transform (...

This paper presents a wavelet transform and Support Vector Machine (SVM) based algorithm for estimating fault location on transmission lines. The Discrete wavelet transform (DWT) is used for data pre-processing and this data are used for training and testing SVM. Five types of mother wavelet are used for signal processing to identify a suitable wavelet family that is more appropriate for use in...

In this paper, we propose an object recognition method for 2D objects using wavelet descriptors. The descriptors are derived from the continuous wavelet transform using the Mexican hat function as mother wavelet. In contrast to the other known methods we apply an angle function to describe object contours extracted as polygons. The contour extraction is based on the object oriented contour extr...