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In this paper, the single-channel EEG based classification systems using simple extracted features are investigated. Each classification system contains the following stages: data acquisition, signal decomposition, feature extraction, and classification. In addition to using the filter bank and empirical mode decomposition (EMD) methods for signal decomposition, a sparse discrete wavelet packet transform...
Coughing is one of the important signs of several diseases in dogs. There are two types of dog cough: dry cough and productive cough. The latter is most often associated with an infectious condition. It is difficult to differentiate between the two types even by experienced practitioners. In this paper, an automatic cough sound classification using neural network is introduced. A discrete wavelet...
A brain-computer interface (BCI) permits cerebral activity alone to control the external devices for assisting people with neuro muscular impairments. Electroencephalogram (EEG) signals are used for brain computer interaction which is highly non-stationary therefore major challenge is to extract features and classify the signals accurately. In this paper we focused on the extraction of features of...
In this paper, A powerful signal processing method wavelet transform is presented to detect power quality events among one of the Artificial intelligence techniques which is Artificial neural networks as a classification system. As a result of the increased applications of non-linear load, it becomes important to find accurate detecting method. Wavelet Transform represents an efficient signal processing...
In this paper, detection method and classification technique of power quality disturbances is presented. Due to the increase of nonlinear load recently, it becomes an essential requirement to insure high level of power supply and efficient commotional consuming. Wavelet Transform represents a powerful mathematical platform which is needed especially at non-stationary situations. Disturbances are fed...
Detection of Power Quality (PQ) is an essential service which many utilities perform for their industrial and large commercial customers. Poor PQ affect the load connected to the supply. It shortens the life of load and can damage the load. It is a difficult task to detect and classify electrical problems which can cause PQ problems. Various types of PQ disturbances are defined in IEEE standards 1159-2009...
The aim of this work is to present an automated method that assists diagnosis of normal and abnormal MR images. The diagnosis method consists of four stages, preprocessing of MR images, feature extraction, dimensionality reduction and classification. After histogram equalization of image, the features are extracted based on discrete wavelet transformation (DWT). Then the features are reduced using...
The aim of this work is to present an automated method that assists diagnosis of normal and abnormal MR images. The diagnosis method consists of four stages, preprocessing of MR images, feature extraction, dimensionality reduction and classification. After histogram equalization of image, the features are extracted based on discrete wavelet transformation (DWT). Then the features are reduced using...
In this study, performance of wavelet transform based features for the speech / music discrimination task has been investigated. In order to extract wavelet domain features, discrete and complex wavelet transforms have been used. The performance of the proposed feature set has been compared with a feature set constructed from the most common time, frequency and cepstral domain features used in speech/music...
MFCC technique is an efficient technique which can be used for speech signals' classification as MFCC can be applied for 1-D signals. This paper suggests a new application for MFCC technique as it can be used for classification of satellite images, which are 2-D objects. Applying MFCC to images, through transforming images to 1-D vectors is an innovation in its own right. The used images for training...
A heart sound feature extraction and classification method has been developed. It used the discrete wavelet decomposition and reconstruction to produce the envelopes of details of the signals for further extracting the features. Some statistical variables were extracted from the processed signals and used as the features for the heart sounds classification. A Multilayer Perceptron Neural Network has...
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