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In this article, the issue of the finite-time anti-synchronization and fixed-time quasi-anti-synchronization for complex-valued neural networks with time-varying delays and leakage delay is explored. First of all, the model is divided into two equivalent real-valued neural networks employing the decomposing technique. Second, by utilizing the Hölder inequality, constructed function and new designed quantized controller, several novel sufficient criteria are obtained to ensure finite-time anti-synchronization of the studied system. In addition, a feedback control strategy is developed to derive some conclusions of quasi-anti-synchronization by applying the Lyapunov function. Meanwhile, the estimated settling time is acquired which does not rely on the initial value. Two methods our paper used to analyze can provide new ideas for future research. Finally, numerical simulation with simulation results is offered to indicate the efficiency and validity of the proposed theoretical results, and the results are applied to the field of image encryption. [ABSTRACT FROM AUTHOR]

In this work, the issue of finite-time synchronization is discussed for complex-valued neural networks (CVNNs) by applying aperiodically intermittent sliding mode control and a non-separation approach. Firstly, to simplify the theoretical analysis process, some new differential inequalities are established, and new estimated time rules are given. Secondly, to avoid the traditional approach of separating CVNNs, a novel complex-valued aperiodically intermittent sliding mode control strategy is designed, which has never been applied to achieve CVNNs synchronization. Furthermore, by adopting the newly established lemmas, novel controllers and Lyapunov functional, some novel finite-time synchronization criteria of CVNNs are acquired. At last, the validity of the resulting conclusions is indicated by some numerical examples. [ABSTRACT FROM AUTHOR]

[Display omitted] • The introduction of potassium bitartrate (KBT) into the TiO 2 film improves TiO 2 surface smoothness and charge transport, reducing recombination centers in PSCs. • KBT in TiO 2 ETLs enhances PSC morphology, reduces interface defects, and improves energy alignment, leading to higher efficiency and stability. • PSCs with KBT show a significant efficiency increase to 23.35 % and maintain over 80 % efficiency after 800 h. The performance of perovskite solar cells (PSCs) has rapidly improved, largely due to advancements in mitigating inherent defects and enhancing interface carrier transport properties. Herein, we provide a facile method to improve the morphology of TiO 2 ETLs, suppress defects at interface, and tailor energy level alignment to enhance carrier separation and extraction efficiency by introducing potassium bitartrate (KBT) into the TiO 2 electron transport layers (ETLs), achieving high-efficiency and stable PSCs. KBT molecules can enhance the surface smoothness of TiO 2 ETLs, resulting in denser and more uniform perovskite films. In addition, the carboxyl groups, hydroxyl groups, and potassium cations containing in KBT improve charge transport efficiency at TiO 2 /perovskite interface by reducing non-radiative recombination centers in TiO 2 and perovskite bottom as well as improving energy level matching. As a result, the target PSC exhibits an obvious improvement in performance with a champion efficiency of 23.35 %, which is greatly improved relative to the control (21.66 %). The long-term operational stability is also remarkably enhanced, after 800 h MPPT, PSCs with KBT remain over 80 % of its initial efficiency. PSCs with KBT-doped ETLs exhibit increased efficiency and stability, highlighting potential of KBT as an interface engineering tool for enhancing PSCs performance. [ABSTRACT FROM AUTHOR]

The traditional leader-follower formation algorithm can realize the formation of multiply robotic fishes, but fails to consider the energy consumption during the formation. In this paper, the energy optimized leader-follower formation algorithm has been investigated to solve this problem. Considering that the acceleration of robotic fish is tightly linked to the motion state and energy consumption, we optimize the corresponding control parameters of the acceleration to reduce energy consumption during the formation via particle swarm algorithm. The whole process has been presented as follows: firstly we realize the formation on the base of the kinematic model with leader-follower formation algorithm; then the energy consumption on the base of dynamical model are derived; finally we seek the optimal control parameters based on the particle swarm optimization (PSO) algorithm. The dynamics simulation of the energy optimization scheme is conducted to verify the functionality of the proposed energy optimized leader-follower formation algorithm via MATLAB. The optimized results demonstrate that the proposed approach, reducing energy consumption during the formation, is superior to the traditional leader-follower formation algorithm and can reduce energy consumption during the formation. The novelty of the work is that we can reduce the energy consumption during the process of formation by considering the energy consumption, which is a gap in the current research field. [ABSTRACT FROM AUTHOR]