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Epilepsy is a chronic neurological disorder which occurs due to the recurring evoking of seizure which results due to the abnormal rhythmic discharge of electrical activities of the brain. This fluctuation in the electrical activities of the brain can be analyzed using EEG signal which provides valuable information about the physiological states of the brain. In this paper we propose an efficient...
In this paper, a new representation method for electrocardiogram (ECG) signals analysis is suggested. This representation scheme is based on the spectral correlation function (SCF) which appears hidden periodicity of signals. The SCF presents a second-order statistical description in the frequency domain and can be used for several applications of ECG analysis such as classification. The SCF of each...
In this paper, we propose a differential reward based online learning algorithm for classifying web pages into predefined topics based on minimal text available in the URLs. It is then compared with two baseline methods, i.e., Support Vector Machine (SVM) and a state-of-the-art Reinforcement Learning Algorithm using recall, precision and F-measure scores. We conducted experiments on large scale Open...
For improving the detection efficiency of hidden information blind detection system, an improved hidden information detection method based rough set theory is proposed against the high dimension of statistical features and high relevance about images. First, an improved general steganalysis system framework is proposed with practical method and steps; second, the Algorithm based on the rough set theory...
In the Network Intrusion Detection, the large number of features increases the time and space cost, besides the irrelative redundant characteristics make the detection accuracy dropped. In order to improve detection accuracy and efficiency, a new Feature Selection method based on Rough Sets and improved Genetic Algorithms is proposed for Network Intrusion Detection. Firstly, the features are filtered...
Identification of voice disorders has been a vital role in our life nowadays. Acoustic analysis can be useful tool to diagnose voice disorders as a complementary technique to other medicine methods such as Laryngoscopy and Stroboscopy. In this paper, we scrutinized feature reduction techniques such as principal component analysis (PCA) and linear discriminant analysis (LDA) as feature subset extraction...
In this paper we propose a new method for feature extraction in the context of still image steganalysis. At first, a denoising algorithm is employed to generate a new version of the observation form the original image. FastICA is employed to separate two sources from the two versions of the input image. Features are extracted from these two estimated sources. At the end support vector machine (SVM)...
To efficiently deal with document classification problem, an efficient document classification algorithm based on kernel local discriminant embedding (kernel LDE) is proposed in this paper. The high-dimensional document data are first mapped into lower-dimensional feature space, then the SVM classifier is applied to classify documents. The experimental results demonstrate that the proposed algorithm...
To efficiently cope with document classification problem, an efficient document classification algorithm based on local discriminant embedding (LDE) and SVM classifier is proposed in this paper. The high-dimensional document space are first projected into the lower-dimensional feature space by using LDE algorithm, the SVM classifier is then applied in the reduced document feature space. Extensive...
Face recognition has received growing attention because of its wide applications. In this paper, an efficient face recognition algorithm based on non-negative matrix factorization (NMF) and SVM is proposed. The high dimension face images are first projected into a lower-dimensional subspace using NMF. The SVM classifier is then used to classify the face image into different classes. The experimental...
Aimed at the problem that many AID algorithms have lower detection rate and higher false alarming rate, a kind of AID algorithm based on multi-SVM classifier is proposed. Also, the framework and flow of this algorithm were designed, and eigenvector constituted by data of the same traffic parameter in some continuous periods was proposed, then the validity and portability were analyzed by simulation...
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