Real-time walking behavior monitoring is essential in ensuring safety and improving people's physical conditions with mobility difficulties. In this paper, a real-time walking motion detection system based on the intelligent walking stick, mobile phone and multi-label imbalance classification method combining focal loss and LightGBM (MFGBoost) is proposed. The Internet of Things (IoT) technology is utilized for communicating between the walking stick and mobile phone. The new MFGBoost is embedded into the Raspberry Pi to classify human motions. MFGBoost is scalable, and other boosting models, such as XGBoost, could also be used as its base classifier. An improved derivation method of the multi-classification focal loss function is proposed in this paper, which is the key to the combination of multi-classification focal loss and Boosting algorithms. We propose a novel denoise method based on window matrix and COPOD algorithm (W-OD). The window matrix is designed to extract data features and smooth noise, and COPOD could output the noise level of the model. A weighted loss function is designed to adjust the model's attention to different samples based on the W-OD algorithm. We evaluate the latest classification model from multiple perspectives on multiple benchmark datasets and demonstrate that MFGBoost and W-OD-MFGBoost could improve classification performance and decision-making efficiency. Experiments conducted on human motion datasets show that W-OD-MFGBoost could achieve more than 97 percent classification accuracy.

This article focuses on the dissipativity-based consensus tracking control (DBCTC) problems of time-varying delayed leader-following nonlinear multiagent systems (LFN-MASs) with event-triggered transmission strategy. The switching topologies of the LFNMASs are subject to uncertain and partially unknown generally Markovian jumping process. The control inputs of the following agents are updated according to the proposed event-triggered transmission strategy, which could reduce the communication burden. Based on the eventtriggered transmission condition and distributed consensus protocol, some dissipativity-based criteria obtained by adopting the delay-product-term Lyapunov-Krasovskii functional (DPTLKF) and higher order polynomial based relaxed inequality (HOPRII) are proposed to guarantee LFNMASs consensus. The validity of the main results is verified by two simulation examples.Index Terms-event-triggered consensus strategy, leaderfollowing nonlinear multiagent systems (LFNMASs), generally uncertain Markovian switching topologies, higher order polynomial based relaxed inequality (HOPRII).

This article focuses on the finite‐time sampled‐data H∞ control problem of Markovian jumping linear system, which consists of mode‐dependent interval time‐varying delays. The delay‐dependent conditions of finite‐time sampled‐data control are obtained by adopting affine Bessel–Legendre inequality and appropriate mode‐dependent Lyapunov–Krasovskii functional. Finally, two examples are displayed to prove the feasibility of the proposed method.

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