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.
The Euclid distance based K-means clustering is among the hard classification algorithms. When dealing with deterministic remote sensing data, it is difficult to gain satisfactory classification results using K-means algorithm. The traditional K-means clustering algorithm is faced with several shortcomings such as locally converged optimization, being sensitive to initial clustering centers, etc....
A novel time domain method based on improved multivariate empirical mode decomposition (MEMD) for plant-wide oscillations characterization is proposed. The original MEMD is ameliorated in the following aspects, (i) decorrelation of the two-dimensional Halton sequences, (ii) boundary processing to restrain end effect and (iii) improved criterion for sifting process stoppage. Due to its capability to...
The acoustic environment of the continental shelf slope waveguide is more complex than those with flat bottoms. For a long receiving array in this area, the amplitude and phase of the received signals will be distortional, leading an attenuation in the spatial correlation of the sound field and a degradation in the array gain of beamformers. This paper shows the performances of three beamformers:...
In this paper, we propose a Long Short-Term Memory Recurrent Neural Network (LSTM-RNN) and multiple kernel learning (MKL) based multi-modal affect recognition scheme (LSTM-MKL). It takes the LSTM-RNN advantage to model the long range dependencies between successive observations, and uses the MKL power to model the non-linear correlations between the inputs and outputs. For each of the affect dimensions...
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.