关键词：
discrete sampling communications;Immersion and Invariance theory;Lyapunov function;multi-agent robotic system
摘要：
The widespread application of multi-agent robotic systems in domains such as agricultural collaboration and automation has accentuated the challenges faced in seeking to achieve rapid synchronization and sustain high-performance control under conditions where velocity states remain unmeasurable. To relieve these challenges, a synchronization control framework is proposed for multi-agent systems, employing non-uniform sampling communication protocols. Initially, a state-variable transformation is applied to construct a composite Lyapunov function that integrates a sampling term. An explicit relation is then derived between the communication interval and the global exponential synchronization rate, thereby establishing a theoretical foundation for the design of non-periodic sampling-based control strategies. Second, a linear-state feedback controller is introduced, which balances convergence speed with the limited frequency of information updates, ensuring asymptotic stability even under prolonged sampling intervals. Third, a velocity observer was designed based on Immersion and Invariance (I&I) theory to solve the problem of unmeasurable velocity states, ensuring the exponential convergence of the estimation error. Finally, the simulation results demonstrate that, with sampling intervals of h is an element of[0.03,0.08] s, the position errors parallel to qi-qd,i parallel to of all six robots converge to below 10-2 within 7 s; meanwhile, the velocity estimation errors decay to nearly zero within 7 s, confirming the effectiveness of the proposed method. The main contributions of this work can be summarized as follows: (1) a new I&I velocity observer is tailored for discrete-time communication; (2) rigorous proof of global exponential convergence is provided via a composite Lyapunov energy function; (3) a reproducible MATLAB simulation framework is presented that enhances both the verifiability and applicability of the proposed approach.
摘要：
In this paper, we propose a novel algorithm that integrates diffusion models with reinforcement learning, called Diffusion-Q Synergy (DQS). The methodology formalizes an equivalence relationship between the iterative denoising process in diffusion models and the policy improvement mechanism in Markov Decision Processes. Central to this framework is a dual-learning mechanism: (1) a parametric Q-function is trained to evaluate noise prediction trajectories through temporal difference learning, effectively serving as a differentiable critic for action quality assessment; and (2) this learned Q-scoring function is then structurally integrated into the training objective of a conditional diffusion model, formulating a constrained optimization problem that simultaneously maximizes expected returns while minimizing policy deviation from behavioral priors. The algorithmic superiority of DQS stems from its hybrid architecture combining the (i) diffusion policy cloning for stable behavior regularization and (ii) adaptive noise rectification through Q-value-guided key denoising step correction, which is particularly effective for refining suboptimal action sequences, thereby guiding the entire diffusion trajectory toward policy optimality. Rigorous ablation studies across benchmark environments demonstrate statistically significant performance improvements (p<0.01) over baseline methods in both computational efficiency and asymptotic policy quality. The implementation has been open-sourced at AOLIGOOD/Diffusion_Q_Synergy, to facilitate reproducibility.
摘要：
Watermelon is a crop susceptible to diseases. Rapid and effective detection of watermelon diseases is of great significance to ensure the yield of watermelon. Aiming at the interference of the environment and obstacles in the natural environment, resulting in low target detection accuracy and poor robustness, this paper takes watermelon leaves as the research object, considering anthracnose, leaf blight, leaf spot and normal leaves as examples. A disease recognition method based on deep learning is proposed. This paper has improved the pre-selected box setting formula of the SSD model and tested it in multiple SSD models. Experiments show that the average accuracy of the final SSD768 model is 92.4%, and the average accuracy of the IOU is 88.9%. It shows that this method can be used to detect watermelon diseases in natural environment.
摘要：
<jats:title>Abstract</jats:title><jats:p>The present study investigates residual contagion of the recent two international crises under the dual functions of “herd effect” and “alarm effects in informatization, focusing on emerging markets. Both the impulse response method and dynamic conditional correlation MGARCH model are used to capture residual contagion from developed markets to emerging markets during the period 2000–2016. The results show that the level of volatility in emerging stock markets was greater than that of developed markets, such as the US and the EU, although they are less integrated with the world. Emerging stock markets are significantly subjected to residual contagion during the US subprime mortgage crisis and Europe’s protracted debt crisis. Moreover, the residual contagion effects of these two crises are noticeably heterogeneous in emerging markets.</jats:p>
期刊：
COMMUNICATIONS IN MATHEMATICAL SCIENCES,2020年18(7):2059-2074 ISSN：1539-6746
通讯作者：
Wang, Yong;Xu, Jiankai
作者机构：
[Tan, Zhong] Xiamen Univ, Sch Math Sci, Xiamen 361005, Fujian, Peoples R China.;[Wang, Yong] South China Normal Univ, South China Res Ctr Appl Math & Interdisciplinary, Guangzhou 510631, Guangdong, Peoples R China.;[Xu, Jiankai] Hunan Agr Univ, Coll Informat Sci & Technol, Changsha 410128, Hunan, Peoples R China.
通讯机构：
[Wang, Yong] S;[Xu, Jiankai] H;South China Normal Univ, South China Res Ctr Appl Math & Interdisciplinary, Guangzhou 510631, Guangdong, Peoples R China.;Hunan Agr Univ, Coll Informat Sci & Technol, Changsha 410128, Hunan, Peoples R China.
关键词：
Axis-symmetric kernel;Integral equation;Non-existence of radial solutions;Regularity lifting lemma
摘要：
Crowd density estimation is one of the critical issues in social activities. The traditional solution to this problem is to leverage video surveillance to monitor a crowd. However, this is not accurate for crowd density estimation because it is still hard to identify people from background. In the past few years, more and more people use Wi-Fi enabled smartphones. Smartphones can send Wi-Fi request packets periodically, even when they are not connected to access points. This gives another promising solution to the crowd density estimation even for the public environment. In this paper, we first develop a Wi-Fi monitor detection that can capture smartphone passive Wi-Fi signal information including MAC address and received signal strength indicator. Then, we propose a positioning algorithm based on smartphone passive Wi-Fi probe and a dynamic fingerprint management strategy. In real-world public social activities, a person may have zero, one, two, or multiple smartphones with variant Wi-Fi signals. Therefore, we design a method of computing the probability of a user generating one Wi-Fi signal to identify people population. Finally, we propose a crowd density estimation solution based on Wi-Fi probe packets positioning algorithm. Experiments were conducted in an indoor laboratory class and three public social activities, clearly demonstrated that the proposed solution can effectively and accurately estimate crowd density.
通讯机构：
[Xu, Jian] H;Huazhong Univ Sci & Technol, Sch Math & Stat, Wuhan 430074, Peoples R China.
摘要：
In the one-dimensional Diophantine approximation, by using the continued fractions, Khintchine's theorem and Jarnik's theorem are concerned with the growth of the large partial quotients, while the improvability of Dirichlet's theorem is concerned with the growth of the product of consecutive partial quotients. This paper aims to establish a complete characterization on the metric properties of the product of the partial quotients, including the Lebesgue measure-theoretic result and the Hausdorff dimensional result. More precisely, for anyx is an element of [0, 1), letx=[a(1),a(2), horizontal ellipsis ] beits continued fraction expansion. The size of the following set, in the sense of Lebesgue measure and Hausdorff dimension,E-m(phi):= {x is an element of [0, 1):a(n)(x) MIDLINE HORIZONTAL ELLIPSISa(n+m-1)(x) >=phi(n) for infinitely manyn is an element of N}, are given completely, wherem >= 1 is an integer and phi: N -> Double-struck capital R(+)is a positive function.
