The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
Today's advanced muscular sensing and processing technologies have made the acquisition of electromyography (EMG) signal which is valuable. EMG signal is the measurement of electrical potentials generated by muscle cells which is an indicator of muscle activity. Other than rehabilitation engineering and clinical applications, EMG signals can also be employed in the field of human computer interaction...
According to the symmetric characteristics of bispectrum, a novel feature extraction scheme, which includes the summation-at-every-column feature vector, the summation-at-every-row feature vector and their combination in a triangle area, one of the 12 symmetric areas of bispectrum, is proposed. By using One-against-One (OAO) method of multi classification of Support Vector Machine (SVM), the mean...
Measured radar data assisted in the successful development and implementation of Specific Emitter Identification (SEI) signal processing algorithms. The aim of the algorithm is the identification of a specific emitter within a single class of emitters. The processes developed are pulse extraction, feature calculation, dimensionality reduction and classification. A pulse is detected whenever the phase...
The paper investigates the feasibility of implementing an intelligent classifier for noise sources in the ocean, with the help of artificial neural networks, using higher order spectral features. Non-linear interactions between the component frequencies of the noise data can give rise to certain phase relations called Quadratic Phase Coupling (QPC), which cannot be characterized by power spectral...
This paper introduces a novel and efficient technique to identify individual radio transmitters with the same model and manufacturing lot. The spurious modulation characteristic of individual radio transmitted signal is used to reflect the unique stray features of individual transmitters, and fractal dimensions of individual signal envelop are utilized to extract the identification feature vector...
This paper presents the audio noise classification using Bark scale features and K-NN technique. This paper uses audio noise signal from NOISEX-92 (12 types). We determine the transfer functions from linear predictive coding (LPC) coefficient of noise signal on Bark scale and use K-NN technique to classify them. The results will be used for optimization of speech recognition model in the presence...
This paper centers on designing a feature-selection algorithm able to provide a ldquosmallrdquo number of adequate features that assist a sound classification system for hearing aids in reducing its computational load without degrading its performance. Because of the problem complexity, we have explored the use of genetic algorithms with restricted search for the mentioned feature selection. In an...
This paper describes a novel method for radar target classification based on high range resolution profile (HRRP). In view of the non-stationary characteristic of radar signal, adaptive Gaussian basis representation (AGR) is utilized to extract features from raw HRRP signatures to fully retain the physics information of target. Then learning vector quantization (LVQ) network is adopted to tackle the...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.