The sea level anomalies(SLAs)pattern in the northwestern Pacific delineated significant differences between La Ni?a events occurring with and without negative Indian Ocean Dipole(IOD)*** the pure La Ni?a events,positi...
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The sea level anomalies(SLAs)pattern in the northwestern Pacific delineated significant differences between La Ni?a events occurring with and without negative Indian Ocean Dipole(IOD)*** the pure La Ni?a events,positive the sea surface level anomalies(SLAs)appear in the northwestern Pacific,but SLAs are weakened and negative SLAs appear in the northwestern Pacific under the contribution of the negative IOD events in 2010/*** negative IOD events can trigger significant westerly wind anomalies in the western tropical Pacific,which lead to the breakdown of the pronounced positive SLAs in the northwestern ***,negative SLAs excited by the positive wind stress curl near the dateline propagated westward in the form of Rossby waves until it approached the western Pacific boundary in mid-2011,which maintained and enhanced the negative phase of SLAs in the northwestern Pacific and eventually,it could significantly influence the bifurcation and transport of the North Equatorial Current(NEC).
This paper addresses the distributed adaptive event-triggered H-infinity filtering problem for a class of sector-bounded nonlinear system over a filtering network with time-varying and switching topology. Both topolog...
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This paper addresses the distributed adaptive event-triggered H-infinity filtering problem for a class of sector-bounded nonlinear system over a filtering network with time-varying and switching topology. Both topology switching and adaptive event-triggered mechanisms (AETMs) between filters are simultaneously considered in the filtering network design. The communication topology evolves over time, which is assumed to be subject to a nonhomogeneous Markov chain. In consideration of the limited network bandwidth, AETMs have been used in the information transmission from the sensor to the filter as well as the information exchange among filters. The proposed AETM is characterized by introducing the dynamic threshold parameter, which provides benefits in data scheduling. Moreover, the gain of the correction term in the adaptive rule varies directly with the estimation error and inversely with the transmission error. The switching filtering network is modeled by a Markov jump nonlinear system. The stochastic Markov stability theory and linear matrix inequality techniques are exploited to establish the existence of the filtering network and further derive the filter parameters. A co-design algorithm for determining H-infinity filters and the event parameters is developed. Finally, some simulation results on a continuous stirred tank reactor and a numerical example are presented to show the applicability of the obtained results.
The rapid progress of foundation models has led to the prosperity of autonomous agents, which leverage the universal capabilities of foundation models to conduct reasoning, decision-making, and environmental interacti...
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The rapid progress of foundation models has led to the prosperity of autonomous agents, which leverage the universal capabilities of foundation models to conduct reasoning, decision-making, and environmental interacti...
The rapid progress of foundation models has led to the prosperity of autonomous agents, which leverage the universal capabilities of foundation models to conduct reasoning, decision-making, and environmental interaction. However, the efficacy of agents remains limited when operating in intricate, realistic environments. In this work, we introduce the principles of Unified Alignment for Agents (UA2), which advocate for the simultaneous alignment of agents with human intentions, environmental dynamics, and self-constraints such as the limitation of monetary budgets. From the perspective of UA2, we review the current agent research and highlight the neglected factors in existing agent benchmarks and method candidates. We also conduct proof-of-concept studies by introducing realistic features to Web-Shop (Yao et al., 2022a), including user profiles to demonstrate intentions, personalized reranking for complex environmental dynamics, and runtime cost statistics to reflect self-constraints. We then follow the principles of UA2 to propose an initial design of our agent and benchmark its performance with several candidate baselines in the retrofitted WebShop. The extensive experimental results further prove the importance of the principles of UA2. Our research sheds light on the next steps of autonomous agent research with improved general problem-solving abilities.
The shockwave signal is affected by the weapon launch and the external environment, and it is often mixed with many kinds of noise, some even submerged. To detect and extract the shockwave signal under low signal-to-n...
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The shockwave signal is affected by the weapon launch and the external environment, and it is often mixed with many kinds of noise, some even submerged. To detect and extract the shockwave signal under low signal-to-noise ratio, the transient signal SNR, the power-law detector of the higher-order cumulant spectrum (HOCS) and the Dual-tree complex wavelet transform (DTCWT) extraction model are proposed in the study. The average power of noise under different SNR was calculated by comparing the average power of the background noise with the instantaneous power of the shockwave. Based on the power-law detection of HOCS, the power-law of the two spectra was analyzed. After the DTCWT, the optimal threshold of the maximum posterior estimation was denoted by layer by layer, then the shockwave signal was extracted by the inverse transform, and the validity of the model was verified by the measured data. Results demonstrate that the signal to noise ratio of the transient signal can reflect the true magnitude of the average power of the noise, and the conventional SNR reduces the average power of the noise, and the error ratio is up to 70%. The power-law detector of bispectrum diagonals has the good effect on Gaussian white noise suppression, and can detect the signal to noise ratio of -15dB. The DTCWT can realize multiple peak shockwave extraction with the smaller amplitude, and the mean square error (MSE) of measured signal extraction can reach 0.0189. The proposed method provides a good reference for the detection of shockwave signal and the extraction of the multi-peak waveform in low signal-to-noise ratio.
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