A text-independent Probabilistic Neural Network (PNN)-based speaker verification system, referred to as WCL-1, is presented. A modular structure, with a distinct PNN for each enrolled speaker, is employed. A gender-dependent universal background model is created to represent the world of possible impostor speakers. Beside portrayal of the WCL-1 system, a comprehensive description of the results...

Artificial neural networks; Sentiment analysis; Text classification; Opinion mining; Support vector machine Abstract The aim of sentiment classification is to efficiently identify the emotions expressed in the form of text messages. Machine learning methods for sentiment classification have been extensively studied, due to their predominant classification performance. Recent studies suggest tha...

This paper presents an algorithm to detect and classify voltage sag causes based on Wavelet Transform (WT) and Probabilistic Neural Network (PNN). A technique is required which is capable of extracting both time-frequency information to identify the causes which contribute to power quality disturbances. Wavelet transform based on multiresolution analysis is used to extract the features from the...

Gas hydrate often occurs in natural gas pipelines and process equipment at high pressure and low temperature. Methanol as a hydrate inhibitor injects to the potential hydrate systems and then recovers from the gas phase and re-injects to the system. Since methanol loss imposes an extra cost on the gas processing plants, designing a process for its reduction is necessary. In this study, an accur...

The progress of research in probabilistic neural network (PNN) and related issues is straight related to directly compare the performance of different PNN algorithm versions. In most cases, the PNN application in real life issues involves the classical activation function (Parzen-Cacoulos estimator) only. Although this estimator has been used in most experimental works so far, it is not the onl...

In this paper, Automation of a power system fault detection using multi resolution analysis (MRA) wavelet transform is proposed and the various coefficients obtained from wavelet transform are given as an input to the probabilistic neural network (PNN). This PNN will classify and find the nature of fault occurring. Later, the decisions obtained from the output of PNN can be used to tune the pow...

The electroencephalogram (EEG) signal plays an important role in the detection of epilepsy. The EEG recordings of the ambulatory recording systems generate very lengthy data and the detection of the epileptic activity requires a timeconsuming analysis of the entire length of the EEG data by an expert. The aim of this work is to develop a new method for automatic detection of EEG patterns using ...

This paper describes automatic detection and classification of visual symptoms affected by fungal disease. Algorithms are developed to acquire and process color images of fungal disease affected on commercial crops like chili, cotton and sugarcane. The developed algorithms are used to preprocess, segment, extract and reduce features from fungal affected parts of a crop. The feature extraction i...