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.
In this paper, we address the problem of automatically recognizing emotions in still images. While most of current work focus on improving whole-image representations using CNNs, we argue that discovering affective regions and supplementing local features will boost the performance, which is inspired by the observation that both global distributions and salient objects carry massive sentiments. We...
Resting-state functional connectivity (rs-FC) analyses have shown that the complex symptoms of schizophrenia are linked to disrupted neural circuits and disconnectivity of intrinsic brain networks. However, these studies assumed temporal stationarity of rs-FCs, while the temporal dynamic of rs-FCs is rarely explored. Here, we test the variability of spontaneous fluctuation in rs-FCs of schizophrenic...
Considering of high transmission rate and short training time, Steady State Visual Evoked Potential (SSVEP) rapidly becomes a practical signal in Brain-Computer Interface(BCI) system. This paper study the extraction method of SSVEP based on the Hilbert-Huang Transformation. The SSVEP was processed by a time-frequency processing system. after empirical mode decomposition and Hilbert-Huang Transform(HHT),...
Recently, there are available laboratory procedures providing useful information to psychiatric diagnostic systems. In this paper, a tensor-based pattern recognition system was used to classify schizophrenic patients and healthy controls. The novel tensor approach is an extension of linear discriminant analysis (LDA). In this method, each subject' structure MRI image was viewed as a tensor sample...
This paper proposes the design method of a Brain-Computer Interface(BCI) system based on SSVEP. Achieved an effective collection and processing of SSVEP information through the combination of analog filtering and digital processing;Changed the features which were extracted from the processed signals into control commands to control the peripherals. In this paper, digital signal processor (DSP) is...
The research designed a brain-computer interface (BCI) system based on the steady state VEP potential (SSVEP). It used the wavelet packet decomposition technology to extract feature. Comparing with the FFT, this method could avoid the spectrum leakage and improve the information transmission rate. A SSVEP-based controlling system of multi-DoF manipulator was presented in this paper on the basis of...
The research adopts the classical visual evoked potentials paradigm, designs the stimulation program and experimental scheme base on the labview platform,and the way of visual stimulate is studied in this paper. In this way we can produce event-related potentials more effectively. On the platform in labview, achieve the event-related potential signal acquisition and processing. Explore how extract...
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.