1,118 research outputs found
HyperDID: Hyperspectral Intrinsic Image Decomposition with Deep Feature Embedding
Full text linkThe dissection of hyperspectral images into intrinsic components through
hyperspectral intrinsic image decomposition (HIID) enhances the
interpretability of hyperspectral data, providing a foundation for more
accurate classification outcomes. However, the classification performance of
HIID is constrained by the model's representational ability. To address this
limitation, this study rethinks hyperspectral intrinsic image decomposition for
classification tasks by introducing deep feature embedding. The proposed
framework, HyperDID, incorporates the Environmental Feature Module (EFM) and
Categorical Feature Module (CFM) to extract intrinsic features. Additionally, a
Feature Discrimination Module (FDM) is introduced to separate
environment-related and category-related features. Experimental results across
three commonly used datasets validate the effectiveness of HyperDID in
improving hyperspectral image classification performance. This novel approach
holds promise for advancing the capabilities of hyperspectral image analysis by
leveraging deep feature embedding principles. The implementation of the
proposed method could be accessed soon at https://github.com/shendu-sw/HyperDID
for the sake of reproducibility.Comment: Submitted to IEEE TGR
A comprehensive thermo-viscoelastic experimental investigation of Ecoflex polymer
Get PDFSilicone polymers have enormous applications, especially in the areas of biomedical engineering. Ecoflex, a commercially available room temperature cured silicone polymer, has attracted considerable attention due to its wide range of applications as medical-grade silicones and as matrix materials in producing nano-filled stretchable sensors and dielectric elastomers for soft robotics. In this contribution, we have conducted a wide range of experiments under thermo-mechanical loadings. These experiments consist of loading-unloading cyclic tests, single-step relaxation tests, Mullins effects tests at different strain rates and stretches, stress recovery tests at different rest time, etc. In order to assess the temperature influences on Ecoflex, a number of viscoelastic tests are performed in a thermal chamber with temperature ranging from -40°C to 140°C. Extensive experimental findings illustrate that Ecoflex experiences a significant stress softening in the first cycles and such a softening recovers gradually with respect to time. It also shows a significant amount of cyclic dissipations at various stretch levels as well as a considerable stress relaxation only for virgin samples. Cyclic dissipations and stress relaxation almost disappear for the case of pre-stretched samples. Furthermore, the material is more or less sensitive under a wide range of temperature differences
A Universal Framework of Superimposed RIS-Phase Modulation for MISO Communication
Full text linkTo fully exploit the additional dimension brought by reconfigurable
intelligent surface (RIS), it is recently suggested by information theory that
modulating information upon RIS phases is able to send extra information with
increased communication rate. In this paper, we propose a novel superimposed
RIS-phase modulation (SRPM) scheme to transfer extra messages by superimposing
information-bearing phase offsets to conventionally optimized RIS phases. The
proposed SRPM is interpreted as a universal framework for RIS phase modulation.
Theoretical union bound of the average bit error rate (ABER) of the proposed
SRPM is also derived with the maximum likelihood (ML) detection. The diversity
order is characterized as 0.5 for all parameter settings, which is useful for
determining the optimal choice of the phase modulation parameters. Furthermore,
we discover that doubling the number of either RIS reflecting elements or the
transmit antennas is equivalent to a 3 dB increment in the transmit power for
SRPM. Numerical results demonstrate the effectiveness of SRPM and reveal that
it achieves reliable communication of more bits than existing schemes.Comment: Accepted by IEEE Transactions on Vehicular Technolog
Superimposed RIS-phase Modulation for MIMO Communications: A Novel Paradigm of Information Transfer
Full text linkReconfigurable intelligent surface (RIS) is regarded as an important enabling
technology for the sixth-generation (6G) network. Recently, modulating
information in reflection patterns of RIS, referred to as reflection modulation
(RM), has been proven in theory to have the potential of achieving higher
transmission rate than existing passive beamforming (PBF) schemes of RIS. To
fully unlock this potential of RM, we propose a novel superimposed RIS-phase
modulation (SRPM) scheme for multiple-input multiple-output (MIMO) systems,
where tunable phase offsets are superimposed onto predetermined RIS phases to
bear extra information messages. The proposed SRPM establishes a universal
framework for RM, which retrieves various existing RM-based schemes as special
cases. Moreover, the advantages and applicability of the SRPM in practice is
also validated in theory by analytical characterization of its performance in
terms of average bit error rate (ABER) and ergodic capacity. To maximize the
performance gain, we formulate a general precoding optimization at the base
station (BS) for a single-stream case with uncorrelated channels and obtain the
optimal SRPM design via the semidefinite relaxation (SDR) technique.
Furthermore, to avoid extremely high complexity in maximum likelihood (ML)
detection for the SRPM, we propose a sphere decoding (SD)-based layered
detection method with near-ML performance and much lower complexity. Numerical
results demonstrate the effectiveness of SRPM, precoding optimization, and
detection design. It is verified that the proposed SRPM achieves a higher
diversity order than that of existing RM-based schemes and outperforms PBF
significantly especially when the transmitter is equipped with limited
radio-frequency (RF) chains.Comment: Submitted to IEEE for possible publicatio
Imperfect CSI: A Key Factor of Uncertainty to Over-the-Air Federated Learning
Full text linkOver-the-air computation (AirComp) has recently been identified as a
prominent technique to enhance communication efficiency of wireless federated
learning (FL). This letter investigates the impact of channel state information
(CSI) uncertainty at the transmitter on an AirComp enabled FL (AirFL) system
with the truncated channel inversion strategy. To characterize the performance
of the AirFL system, the weight divergence with respect to the ideal
aggregation is analytically derived to evaluate learning performance loss. We
explicitly reveal that the weight divergence deteriorates as
as the level of channel estimation accuracy
vanishes, and also has a decay rate of with the increasing
number of participating devices, . Building upon our analytical results, we
formulate the channel truncation threshold optimization problem to adapt to
different , which can be solved optimally. Numerical results verify the
analytical results and show that a lower truncation threshold is preferred with
more accurate CSI.Comment: Submitted to IEEE for possible publicatio
Influence of initial microcracks on the dynamic mechanical characteristics of sandstone
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Multi-Global Navigation Satellite System (GNSS) real-time tropospheric delay retrieval based on state-space representation (SSR) products from different analysis centers
Get PDFThe troposphere plays an important role in a range of weather and various climate changes. With the development of the Global Navigation Satellite System (GNSS), the zenith tropospheric delay (ZTD) retrieval using GNSS technology has become a popular method. Research on ZTD accuracies of state-space representation (SSR) corrections from different analysis centers derived from real-time precise point positioning (RT-PPP) is important for Earth observation correction, meteorological disaster forecasting, and warning with the increasing abundance of state-space representation (SSR) products obtained by the International GNSS Service (IGS) analysis center. Therefore, accuracies and availability of real-time orbits and clock errors obtained by the Chinese Academy of Sciences (CAS), GMV Aerospace and Defense (GMV), Centre National d'Etudes Spatiales (CNE), and Wuhan University (WHU) are evaluated, and the RT positioning performance and ZTD accuracies are analyzed for Global Positioning System (GPS), Galileo (GAL), and BeiDou Navigation Satellite System-3 (BDS3) satellites. The results indicate that CAS has the higher satellite availability, providing SSR corrections for 82 GPS, Galileo, and BDS3 satellites. The accuracies of GPS, Galileo, and BDS3 orbits are best at WHU, CAS, and WHU with values of 5.57, 5.91, and 11.77 cm, respectively; the standard deviations (SDs) of clock error are all better than 0.22, 0.19, and 0.55 ns, and the root mean square errors (RMSEs) are better than 0.54, 0.32, and 1.46 ns. CAS has the best signal-in-space ranging errors (SISREs) followed by WHU, while CNE and GMV are worse. In the RT-PPP test, convergence times for CAS and WHU are 14.9 and 14.4 min, respectively, with 3D positioning accuracy for both of around 3.3 cm, which is better than for CNE and GMV. Among them, WHU SSR has the higher accuracy of RT-PPP-derived ZTD, with an RMSE of 6.06 mm and desirable availability with a completeness rate of 89 %.</p
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