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This work is an evaluation, to which degree geological information can be obtained from modern remote sensing systems like the multispectral ASTER or the hyperspectral Hyperion sensor for a volcanic region like Teide Volcano (Tenerife, Canary Islands). To account for the enhanced information content these sensors provide, hyperspectral analysis methods, incorporating for example Minimum Noise Fraction-Transformation...
Ground penetrating radar has been widely used in many areas. However, the processing and interpretation of acquired signals remains a challenging task since it requires experienced users to manage the whole operations. In this paper, we propose an automatic classification system to categorise GPR signals based on magnitude spectrum amplitudes and support vector machines. The system is tested on a...
The classification of unstructured P2P multicast video streaming is the premise for playing online linkage and real-time evidence in the process of network monitoring management. A new classification method is demonstrated, and some real-time protocol behavior features are figured in this paper, which is found out through distinguishing packet type and transmission direction. With these accessible...
Objective: To realize the automatic classification between melancholic and healthy persons by extracting the disease features from the melancholic's EEG signals. Methods: 1. Extracting the features from the EEG signals of melancholic and healthy persons; 2. Obtaining the characteristic parameters such as the maximum, minimum, mean and standard deviation of EEG power spectrum amplitude; 3. Training...
Optimizing a classifier is a subject of great interest in the research area. A lot of methods inspired of biological metaphors are proposed for this task. This paper present a new algorithm based on the natural immune metaphors which select a proper subset of features and optimal parameters of a support vector machines (SVM) classifier. The designed optimization method is validated for ERP assessment...
Classifying the motion of the five fingers of the hand using non-invasive bio-signal readings from the forearm is still an unsolved research challenge. Its solution is relevant to hands-free remote control devices, on-stage live performances, consumer entertainment, the video game industry, and most importantly the design of hand prosthetics for amputees. This paper proposes a solution that uses the...
This paper address on the classification of mental task EEG signals, which is one of the key issues of Brain-Computer Interface (BCI). We proposed a method using wavelet packet entropy and Support Vector Machine (SVM). First, we apply 7 levels wavelet packet decomposition to each channel of EEG with db4. After extraction four spectrum bands (delta,thetas,alpha, beta), an entropy algorithm was performed...
While magnetoencephalography (MEG) is widely used to identify spatial locations of brain activations associated with various tasks, classification of single trials in stimulus-locked experiments remains an open subject. Very significant single-trial classification results have been published using electroencephalogram (EEG) data, but in the MEG case, the weakness of the magnetic fields originating...
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