Serwis Infona wykorzystuje pliki cookies (ciasteczka). Są to wartości tekstowe, zapamiętywane przez przeglądarkę na urządzeniu użytkownika. Nasz serwis ma dostęp do tych wartości oraz wykorzystuje je do zapamiętania danych dotyczących użytkownika, takich jak np. ustawienia (typu widok ekranu, wybór języka interfejsu), zapamiętanie zalogowania. Korzystanie z serwisu Infona oznacza zgodę na zapis informacji i ich wykorzystanie dla celów korzytania z serwisu. Więcej informacji można znaleźć w Polityce prywatności oraz Regulaminie serwisu. Zamknięcie tego okienka potwierdza zapoznanie się z informacją o plikach cookies, akceptację polityki prywatności i regulaminu oraz sposobu wykorzystywania plików cookies w serwisie. Możesz zmienić ustawienia obsługi cookies w swojej przeglądarce.
The present study focuses on the selection of appropriate wavelet basis which would result in better classification of Power Quality (PQ) events. The accuracy of the classification is often critically dependent on the nature of wavelet basis and the induction algorithm. This study, therefore, comprehensively investigates the performance of several wavelet families including Daubechies, Coiflets, Symlets,...
In this study, EEG data recorded during mental arithmetic operations and silent reading were analyzed by discrete wavelet transform and feature vectors were obtained. The obtained feature vectors are classified by Support Vector Machines (SVM). Results are given for 26 channels, all recorded channels, and for 10 most effective channels. Correlation based feature selection based algorithm is used for...
The aim of this study was to detect sleep stages of human by using EEG signals. In accordance with this purpose, discrete wavelet transforms (DWT) and empirical mode decomposition (EMD) were separately used for feature extraction. Subcomponents of EEG signals obtained by the two methods were assumed as feature vectors. Statistical parameters were used to reduce dimension of feature vectors. The same...
The research interest in fetal heart rate (FHR) monitoring dates back to the 1960s, and the breakthrough on fetal surveillance has been seen during the 1990s with computerized systems. Notwithstanding the general use of cardiotocography (CTG) in fetal monitoring, the assessment of fetal well-being exhibits a significant inter- and even intraobserver variability. Computerized CTG analysis has seen...
The increasing number of polluting loads requires higher power quality (PQ) in the generation, transmission and distribution systems. In order to improve the power quality, the power disturbances should be monitored continuously. Power quality monitoring and analysis must be able to detect and classify the disturbances on the electrical system. A new method for optimal features selection and classification...
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...
Malignant melanoma is reported to be the deadliest of skin cancers. Therefore, early diagnosis is crucial for reducing of melanoma-related deaths. Medical Informatics uses the computer technology such as Computer Aided Diagnosis (CAD) for melanoma diagnostic. This paper presents computational intelligence approaches namely, Artificial Neural Network (ANN) and Adaptive-Network-based Fuzzy Inference...
Emotion plays an important role in human daily life and is a significant feature for interaction among people. Due to having adaptive role, it motivate human to respond stimuli in their environment quickly for improving their communication, learning and decision-making. With increasing role of brain computer interface (BCI) in interaction between users and computer, automatic emotion recognition has...
The Electrocardiogram is a tool used to access the electrical recording and muscular function of the heart and in last few decades it is extensively used in the investigation and diagnosis of heart related diseases. It must be noted that the heart rate fluctuates not only because of cardiac demand, however is also influenced as a result of the occurrence of arrhythmias, diabetes and other cardiac...
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...
Magnetic resonance imaging (MRI) is a kind of imaging modality, which offers clearer images of soft tissues than computed tomography (CT). It is especially suitable for brain disease detection. It is beneficial to detect diseases automatically and accurately. We proposed a pathological brain detection method based on brain MR images and online sequential extreme learning machine. First, seven wavelet...
This paper presents a hybrid detection method and classification Technique based on Hilbert-Huang Transform (HHT) and Feed Forward Neural Networks (FFNNs) to improve the efficient delivery and ensure accurate detection of quality disturbances in the electrical power grids. First, quantities characteristics of power quality disturbances (PQDs) are introduced according its parametrical conditions. Thereafter,...
In modern days, Cancer is spreading rapidly which requires a significant attention along with its proper detection and identification, which is even more crucial. Attempt should be made to detect it an early stage so that it may be controlled and sometimes cured. But this requires proper diagnosing methods so that the demerits and pains of being diagnosed are minimized among patients. With respect...
This paper implemented wavelet transforms integrated with a fuzzy logic system to classify all 11 types of faults in transmission line without compensation. The proposed scheme uses only two successive cycles (one cycle pre and one cycle post fault samples) of the three phase current signals to estimate ground current signal at one end. Energy is obtained by decomposition of discrete wavelet transforms...
In this paper a novel brain-computer interface based on the gaze on rotating vane using five channels of EEG signal is proposed. Classification of EEG signal is done in three sessions: 1-when vane rotates fast and slow in an anti-clockwise manner, 2-when vane rotates slow in a clockwise and rotates fast in an anti-clockwise manner, 3-when vane rotates slow in a clockwise and rotates slow in an anti-clockwise...
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 recent years, researchers have recognized relational tables on the Web as an important source of information. To assist this research we developed the Dresden Web Tables Corpus (DWTC), a collection of about 125 million data tables extracted from the Common Crawl (CC) which contains 3.6 billion web pages and is 266TB in size. As the vast majority of HTML tables are used for layout purposes and only...
This work analyzes the suitability of spectral features in the Dual Tree Complex Wavelet Transform (DT-CWT) domain for EEG signal analysis by propounding a DT-CWT based feature extraction scheme. Unlike discrete wavelet transform-DT-CWT ensures limited redundancy and provides approximate shift invariance. To demonstrate the efficacy of DT-CWT for EEG signal analysis, it is applied in conjunction with...
In this work, Dual Tree Complex Wavelet Transform (DT-CWT) is introduced to devise an effective feature extraction scheme for physiological signal analysis. Unlike discrete wavelet transform- DT-CWT ensures limited redundancy and provides approximate shift invariance. To demonstrate the efficacy of DT-CWT for physiological signal analysis, it is applied in conjunction with spectral features to propound...
Podaj zakres dat dla filtrowania wyświetlonych wyników. Możesz podać datę początkową, końcową lub obie daty. Daty możesz wpisać ręcznie lub wybrać za pomocą kalendarza.