this paper presents the application of radial basis neural networks to the development of a novel method for the condition monitoring and fault diagnosis of synchronous generators. in the proposed scheme, flux linkage analysis is used to reach a decision. probabilistic neural network (pnn) and discrete wavelet transform (dwt) are used in design of fault diagnosis system. pnn as main part of thi...

This paper presents the application of radial basis neural networks to the development of a novel method for the condition monitoring and fault diagnosis of synchronous generators. In the proposed scheme, flux linkage analysis is used to reach a decision. Probabilistic neural network (PNN) and discrete wavelet transform (DWT) are used in design of fault diagnosis system. PNN as main part of thi...

handwritten digit recognition can be categorized as a classification problem. probabilistic neural network (pnn) is one of the most effective and useful classifiers, which works based on bayesian rule. in this paper, in order to recognize persian (farsi) handwritten digit recognition, a combination of intelligent clustering method and pnn has been utilized. hoda database, which includes 80000 p...

In this paper, a probabilistic neural network (PNN) based classifier is used to judge the static security of the power system. The proposed classifier classifies the security of the power system based on the voltage profile of each bus in reference to changes in the generation and load profile in the system. The probabilistic neural network is used and compared with the radial basis function ne...

In this paper, the processing of sonar signals has been carried out using Minimal Resource Allocation Network (MRAN) and a Probabilistic Neural Network (PNN) in differentiation of commonly encountered features in indoor environments. The stability-plasticity behaviors of both networks have been investigated. The experimental result shows that MRAN possesses lower network complexity but experien...

In this paper, the processing of sonar signals has been carried out using Minimal Resource Allocation Network (MRAN) and a Probabilistic Neural Network (PNN) in differentiation of commonly encountered features in indoor environments. The stability-plasticity behaviors of both networks have been investigated. The experimental result shows that MRAN possesses lower network complexity but experien...

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 ...

Feature extraction and accurate classification of the emotion-related EEG-characteristics have a key role in success of emotion recognition systems. In this paper, an optimal EEG-based emotion recognition algorithm based on spectral features and neural network classifiers is proposed. In this algorithm, spectral, spatial and temporal features are selected from the emotion-related EEG signals by...

Probabilistic Neural Network (PNN) also termed to be a learning machine is preliminarily used with an extension of various image classifications based on Training networks and Testing networks. To efficiently detect Brain Tumor cells, clustering method based on FCM can also be implemented. The Probabilistic Neural Network (PNN) will be employed to classify the various stages of Tumor cut levels...

Advanced Probabilistic Neural Network for the Prediction of Concrete Strength Doo Kie Kim1, Seong Kyu Chang1 and Sang Kil Chang1 Summary Accurate and realistic strength estimation before the placement of concrete is highly desirable. In this study, the advanced probabilistic neural network (APNN) was proposed to reflect the global probability density function by summing the heterogeneous local ...