In this paper we report a novel application-based model as a suitable alternative for the classification and identification of attacks on a computer network, and thus guarantee its safety from HTTP protocol-based malicious commands. The proposed model is built on a self-recurrent neural network architecture based on wavelets with multidimensional radial wavelons, and is therefore suited to work...

This paper demonstrates classification of PQ events utilizing wavelet transform (WT) energy features by artificial neural network (ANN) and SVM classifiers. The proposed scheme utilizes wavelet based feature extraction to be used for the artificial neural networks in the classification. Six different PQ events are considered in this study. Three types of neural network classifiers such as feed ...

The induction motors effort to widely industrial fields. On the contrary, faults of the induction motors cause another faults of the whole system, because the faults of the induction motors often progress through long time. It is very important that diagnosis for diagnosis fault and extracted fault feature from the acquired signal using wavelet transform. Extracted features use the fault diagno...

simulation of groundwater fluctuations plays a crucial role in management of watersheds and water demand balancing. recently, wavelet analysis has been used widely in time series decomposition and coupling with neural networks for hydrological modeling. in this paper, the ability of the wavelet-dynamic artificial neural networks (w-ann) model was applied in forecasting one-month-ahead of ground...

‘Steganography is a art, which enforcing for obscur one part of data or information within another’. this paper shown an image steganography scheme which based on neural network fusion in wavelet transform domain. The cover and stego image is dividing in its frequency coefficients components by wavelet transform domain, and neural network used as classifier. This paper performed on the 256*256 ...

This work presents results of the use of a wavelet filter for noise reduction and data compression of signals generated by artificial nose sensors. To verify the performance of the wavelet analysis in the treatment of odor patterns, we compare two widely used artificial nose classifiers, multi-layer perceptron neural network and time delay neural network in the analysis of signals generated by ...

Wavelet analysis as a recently data filtering method (or multi-scale decomposition) is particularly useful for describing signals with sharp spiky, discontinuous or fractal structure in financial markets. This study investigates the optimal several wavelet thresholding criteria or techniques to support the multi-signal decomposition methods of a daily Korean won / U.S. dollar currency market as...

This paper proposed ship classification based on covariance of discrete wavelet using probability Neural Network A set of ship profiles are used to build a covariance matrix by discrete wavelet transform using Neural Network. It is found that this method for ship classifier design offers good class discriminacy when trained with 5 ship classes. This method can discriminate noisy ship very well....

Abstract—This paper presented a video watermarking algorithm based on wavelet chaotic neural network. First, to enhance binary image’s security, the algorithm encrypted it with double chaotic based on Arnold and Logistic map, Then, the host video was divided into some equal frames and distilled the key frame through chaotic sequence which generated by Logistic. Meanwhile, we distilled the low f...

This work compares and contrasts results of classifying time-domain ECG signals with pathological conditions taken from the MIT– BIH arrhythmia database. Linear discriminant analysis and a multi-layer perceptron were used as classifiers. The neural network was trained by two different methods, namely back-propagation and a genetic algorithm. Converting the time-domain signal into the wavelet do...