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An automatic recognize method of the subcarrier modulation signals is presented in this paper. The specific model of subcarrier modulation signals is described. The features based on the model are introduced. The classification algorithm using the features is analyzed by the simulation and actual signals. The real-time monitoring system in ultrahigh frequency can utilize the proposed algorithm to...
Music emotion is a special emotion that is aroused by music which is a media that can convey human affection. Music emotion classification is a popular topic in recent years. The mood of a music clip describes emotional expression. It is helpful in music understanding, music retrieval and some other interesting music related application. In this paper, a method is proposed using a framework named...
The aim of this study is to develop and evaluate an algorithm to help in the diagnosis of the obstructive sleep apnea syndrome (OSAS). Arterial oxygen saturation (SaO2) signals from nocturnal pulse oximetry were used to identify OSAS patients. A total of 149 SaO2 recordings from subjects suspected of OSAS were available. The initial population was divided into a training set (74 subjects) and a test...
Perceptual errors such as repetition blindness (RB) and attentional blink (AB) can affect the morphology of the target-P300. These perceptual errors may occur with the use of the Farwell & Donchin P300 speller protocol and in turn interfere with the desired symbol identification. In this paper a state of the art classification algorithm is employed to classify brain-computer interface (BCI) competition...
A classification algorithm for environmental sound recordings or ldquosoundscapesrdquo is outlined. An ant clustering approach is proposed, in which the behavior of the ants is governed by fuzzy rules. These rules are optimized by a genetic algorithm specially designed in order to achieve the optimal set of homogeneous clusters. Soundscape similarity is expressed as fuzzy resemblance of the shape...
The purpose of this paper is to analyze the electroencephalogram (EEG) signals of imaginary left and right hand movements, an application of brain-computer interface (BCI). We propose here to use an adaptive neuron- fuzzy inference system (ANFIS) as the classification algorithm. ANFIS has an advantage over many classification algorithms in that it provides a set of parameters and linguistic rules...
In this paper, we investigate identification of human subjects from electrocardiogram (ECG) signals. We segment the ECG records into individual heartbeat based on the localization of R wave peaks. Two types of features, namely analytic and appearance features, are extracted to represent the characteristics of heartbeat signal of different subjects. Feature selection is performed to find out significant...
To satisfy the difficult requirements of ECG analysis such as large data volume, high accuracy and real-time, a classification algorithm for arrhythmia based on clustering analysis is developed. According to things-of-one-kind-come-together principle, this algorithm uses the similarity of heart cases of the same category and, at the same time, incorporates the factor of individual differences. It...
A classification algorithm is developed to translate facial movements into five cursor actions: i) left, ii) right, iii) up, iv) down, and v) left-click. The algorithm utilizes the unique spectral characteristics exhibited by electromyogram (EMG) signals obtained from different muscles in the face to assist in the classification process. A previous three-electrode, EMG-based system was utilized in...
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