Signal Processing
The drawback of inter-subcarrier interference in OFDM systems makes the channel estimation and signal detection performance of OFDM systems with few pilots and short cyclic prefixes (CP) poor. Thus, we use deep learning to assist OFDM in recovering nonlinearly distorted transmission data. Specifically, we use a self-normalizing network (SNN) for channel estimation, combined with a convolutional neural network (CNN) and a bidirectional gated recurrent unit (BiGRU) for signal detection, thus proposing a novel SNN-CNN-BiGRU network structure (SCBiGNet).
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212 Views
The data collection questionnaire consisted of two sections. One section involved the collection of data via Google Forms questionnaires, and the other involved the collection of WhatsApp voice samples. There were three subsections in the questionnaire section. The first consisted of the individual's basic information, such as email address, name, and identification number. The second was the personal health questionnaire depression scale (PHQ8), which included 8 groups of statements, and the third was the Beck Depression Inventory-II, which contained 21 groups of statements.
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816 Views
<p>Two-electrode straight open magnetic source (TSOMS) has been widely used on the magnetic minesweeper and magnetic decoy. Fast-forward modeling and obtaining the high-precision magnetic field in the air are the prerequisites for real-time inversion and positioning of the TSOMS. In this paper, we propose an algorithm to calculate the magnetic field of the two-electrode straight open magnetic source (MFTSOMS) by previous theoretical research. And a classical algorithm of electric dipole magnetic field is used to verify the correctness of our algorithm.
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83 Views
A multi-scale attention based channel estimation framework is proposed for reconfigurable intelligent surface (RIS) aided massive multiple-input multiple-output systems, in which both hardware imperfections and time-varying characteristics of cascaded channel are investigated. By exploiting the spatial correlations of different scales in the RIS reflection element domain, we construct a Laplacian pyramid attention network (LPAN) to realize the high-dimensional cascaded channel reconstruction with limited pilot overhead.
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540 Views
These data is state estimation accuracy of the proposed algorithm When the equivalent measurement loss probability is 0.1
These data includes the position estimation accuracy and velocity estimation accuracy of the algorithm.
The data are explained below:
save_bikf_pos_p1, save_kf_pos_p1, save_okf_pos_p1, save_bakf_pos_p1, save_vakf_pos_p1 are the position accuracy of the BKF, KF, OKF, the proposed BAKF-GIWM and the VAKF-GIWM, respectively.
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80 Views
Surface EMG (sEMG) signals collected during activities of daily life (ADL) provide better insights toward understanding neuromuscular disorders, persons with limb disabilities, aging adults and neuromotor deficits. Hand movement and control mechanism analysis may improve the design of prosthetic devices, realistic biomechanical hands, and rehabilitation therapy. We present a sEMG signal database corresponding to the Indian population.
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1903 Views
We present Vocal92, a multivariate Cappella solo singing and speech audio dataset spanning around 146.73 hours sourced from volunteers. To the best of our knowledge, this is the first dataset of its kind that specifically focuses on a cappella solo singing and speech. Furthermore, we use two current state-of-the-art models to construct the singer recognition baseline system.
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40 Views
Typically, control strategies for legged robots have been developed to adapt their leg movements to deal with complex terrain. When the legs are extended in search of ground contact to support the robot body, this can result in the center of gravity (CoG) being raised higher from the ground and can lead to unstable locomotion if it deviates from the support polygon. An alternative approach is body adaptation, inspired by millipede/centipede locomotion behavior, which can result in low ground clearance and stable locomotion.
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212 Views
Personal assistive devices for rehabilitation will be in increasing demand during the coming decades due to demographic change, i.e., an aging society. Among the elderly population, difficulty in walking is the most common problem. Even though there are commercially available lower limb exoskeleton systems, the coordination between user and device still needs to be improved to achieve versatile personalized gait. To tackle this issue, an advanced EXOskeleton framework for Versatile personalized gaIt generation with a Seamless user-exo interface (called "EXOVIS") is proposed in this study.
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407 Views
This is a data set for Radio Frequency fingerprinting, which is a kind of identification of wireless devices based on their intrinsic physical features. The data set is composed by GSM bursts collected from 12 GSM mobile phones while transmitting. The samples have been collected using a Software Defined Radio with a sample rate at 20 MS/s. The content information has been removed from the bursts to remove the risk of bias due to content. The data set is in MATLAB format.
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1031 Views