This paper focuses on the challenge of fixed-time control for spatiotemporal neural networks(SNNs) with discontinuous activations and time-varying coefficients. A novel fixed-time convergence lemma is proposed, which ...
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This paper focuses on the challenge of fixed-time control for spatiotemporal neural networks(SNNs) with discontinuous activations and time-varying coefficients. A novel fixed-time convergence lemma is proposed, which facilitates the handling of time-varying coefficients of SNNs and relaxes the restriction on the non-positive definiteness of the derivative of the Lyapunov function. Besides, a more flexible and economical aperiodically switching control technique is presented to stabilize SNNs within a fixed time,efectively reducing the amount of information transmission and control costs. Under the newly established fixed-time convergence lemma and aperiodically switching controller, many more general algebraic conditions are deduced to ensure the fixed-time stabilization of SNNs. Numerical examples are provided to manifest the validity of the results.
THE development of agriculture faces significant challenges due to population growth, climate change, land depletion, and environmental pollution, threatening global food security [1]. This necessitates the developmen...
THE development of agriculture faces significant challenges due to population growth, climate change, land depletion, and environmental pollution, threatening global food security [1]. This necessitates the development of sustainable agriculture, where a fundamental step is crop breeding to improve agronomic or economic traits, e.g., increasing yields of crops while decreasing resource usage and minimizing pollution to the environment [2].
An innovative strategy was proposed by integration of membrane contactor(MC)with biphasic solvent for efficient CO_(2) capture from flue *** accessible fly ash-based ceramic membrane(CM)underwent hydrophobic modificat...
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An innovative strategy was proposed by integration of membrane contactor(MC)with biphasic solvent for efficient CO_(2) capture from flue *** accessible fly ash-based ceramic membrane(CM)underwent hydrophobic modification through silane grafting,followed by fluoroalkylsilane decoration,to prepare the superhydrophobic membrane(CSCM).The CSCM significantly improved resistance to wetting by the biphasic solvent,consisting of amine(DETA)and sulfolane(TMS).Morphological characterizations and chemical analysis revealed the notable enhancements in pore structure and hydrophobic chemical groups for the modified *** of wetting/bubbling behavior based on static wetting theory referred the liquid entry pressure(LEP)of CSCM increased by 20 kPa compared to pristine *** with traditional amine solvents,the biphasic solvent presented the expected phase *** experiments demonstrated that the CO_(2) capture efficiency of the biphasic solvent increased by 7%,and the electrical energy required for desorption decreased by 32%.The 60-h continuous testing and supplemental characterization of used membrane confirmed the excellent adaptability and durability of the *** study provides a potential approach for accessing hydrophobic ceramic membranes and biphasic solvents for industrial CO_(2) capture.
COMPUTATIONAL knowledge vision [1] is emphasized as a novel perspective or field in this paper. It first proposes the visual hierarchy and its connection to knowledge, stating that knowledge is a justified true belief...
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COMPUTATIONAL knowledge vision [1] is emphasized as a novel perspective or field in this paper. It first proposes the visual hierarchy and its connection to knowledge, stating that knowledge is a justified true belief. To further the previous research, we concisely summarize our recent works and suggest a new direction that knowledge is also a thought framework in vision.
Unmanned systems are increasingly adopted in various fields,becoming an indispensable technology in daily *** systems are the lifeblood of unmanned systems,and affect the working time and task ***,traditional power sy...
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Unmanned systems are increasingly adopted in various fields,becoming an indispensable technology in daily *** systems are the lifeblood of unmanned systems,and affect the working time and task ***,traditional power systems,such as batteries and fuels have a fixed ***,once the power supply is exhausted and cannot be replenished in time,the unmanned systems will stop ***,researchers have increasingly begun paying attention to renewable energy generation *** principles,advantages,and limitations of renewable energy generation technologies are different,and their application effects in different unmanned systems are also *** paper presents a comprehensive study of the application and development status of photovoltaic,thermoelectric,and magnetoelectric generation technologies in four kinds of unmanned systems,including space,aviation,ground,and water,and then summarizes the adaptability and limitations of the three technologies to different ***,future development directions are predicted to enhance the reliability of renewable energy generation technologies in unmanned *** is the first study to conduct a comprehensive and detailed study of renewable energy generation technologies applied in unmanned *** present work is critical for the development of renewable energy generation technologies and power systems for unmanned systems.
This paper is concerned with the distributed resilient fusion filtering(DRFF)problem for a class of time-varying multi-sensor nonlinear stochastic systems(MNSSs)with random sensor delays(RSDs).The phenomenon of the RS...
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This paper is concerned with the distributed resilient fusion filtering(DRFF)problem for a class of time-varying multi-sensor nonlinear stochastic systems(MNSSs)with random sensor delays(RSDs).The phenomenon of the RSDs is modeled by a set of random variables with certain statistical *** addition,the nonlinear function is handled via Taylor expansion in order to deal with the nonlinear fusion filtering *** aim of the addressed issue is to propose a DRFF scheme for MNSSs such that,for both RSDs and estimator gain perturbations,certain upper bounds of estimation error covariance(EEC)are given and locally minimized at every sample *** the light of the obtained local filters,a new DRFF algorithm is developed via the matrix-weighted fusion ***,a sufficient condition is presented,which can guarantee that the local upper bound of the EEC is ***,a numerical example is provided,which can show the usefulness of the developed DRFF approach.
Incident particles in the Klein tunnel phenomenon in quantum mechanics can pass a very high potential *** the concept of tunneling into the analysis of phononic crystals can broaden the application *** this study,the ...
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Incident particles in the Klein tunnel phenomenon in quantum mechanics can pass a very high potential *** the concept of tunneling into the analysis of phononic crystals can broaden the application *** this study,the structure of the unit cell is designed,and the low frequency(<1 k Hz)valley locked waveguide is realized through the creation of a phononic crystal plate with a topological phase transition *** defect immunity of the topological waveguide is verified,that is,the wave can propagate along the original path in the cases of impurities and ***,the tunneling phenomenon is introduced into the topological valley-locked waveguide to analyze the wave propagation,and its potential applications(such as signal separators and logic gates)are further explored by designing phononic crystal *** research has broad application prospects in information processing and vibration control,and potential applications in other directions are also worth exploring.
Lake eutrophication in cold and arid regions is showing a deepening trend in recent years,posing a serious threat to the regional ecological *** occurrence characteristics,bioavailability,sorption-desorption character...
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Lake eutrophication in cold and arid regions is showing a deepening trend in recent years,posing a serious threat to the regional ecological *** occurrence characteristics,bioavailability,sorption-desorption characteristics,and release risk of sediment nitrogen in the Ulanor Wetland,located in the Hulun Lake basin of China,were investigated by combining field investigation,laboratory simu-lation experiments,and multiple technologies,including diffusive gradients in thin films and high-resolution dialysis *** total nitrogen(TN)in the water overlying the sediment bed(i.e.,overlying water)ranged from 1.44 to 2.65 mg/*** inorganic nitrogen was the main form of TN in overlying water,and ammonia nitrogen(NH4+-N)in the pore water at the sediment-water interface was higher than that in the overlying *** sediment TN content ranged from 695.37 to 2,344.77 mg/kg,with acid-dissolved nitrogen as the main component,and can cause the lowest level of ecotoxic effect The maximum and equilibrium adsorption amounts of sediment NH4+-N ranged from 0.269 to 1.017 mg/g and 0.0132-0.0382 mg/g,*** bioavailability and transport capacity of sediment nitrogen were relatively weak,but a release risk was still observed.
Dear Editor,Light fields give relatively complete description of scenes from perspective of angles and positions of rays. At present time, most of the computer vision algorithms take 2D images as input which are simpl...
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Dear Editor,Light fields give relatively complete description of scenes from perspective of angles and positions of rays. At present time, most of the computer vision algorithms take 2D images as input which are simplified expression of light fields with depth information discarded. In theory, computer vision tasks may achieve better performance as long as complete light fields are acquired.
Dear Editor,This letter focuses on leveraging the object information in images to improve the performance of the U-Net based change *** detection is fundamental to many computer vision *** existing solutions based on ...
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Dear Editor,This letter focuses on leveraging the object information in images to improve the performance of the U-Net based change *** detection is fundamental to many computer vision *** existing solutions based on deep neural networks are able to achieve impressive results.
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