The soft fault diagnosis of nonlinear analog circuits is an important guarantee of the stable and reliable operation of electronic products. In view of the low accuracy and heavy computation load of current soft fault diagnosis methods for nonlinear analog circuits, this paper presents a soft fault diagnosis method for nonlinear analog circuits based on fractal theory. Analyzing the single-frac...

Improving out-of-sample forecasting is one of the main issues in financial research. Previous studies have achieved this objective by increasing the number of input variables or changing the kind of input variables. Changing the forecasting model is another possible approach to improve out-of-sample forecasting. Most researches have focused on linear models, while few have studied nonlinear mod...

The consensus control problem of multi-agent systems (MASs) is studied. Firstly, a predefined-time algorithm proposed for nonlinear uncertain with the input delay and switching topology. Then, resource consumption considered, dynamic event-triggered presented by introducing internal variables, which can make MASs achieve in preset time. correctness proved algebraic graph theory Lyapunov theory,...

The problem of robust adaptive stabilization of a class of multi-input multi-output nonlinear systems with constant linearly parameterized uncertainty and unknown structure of bounded variation have been considered. With the aid of direct adaptive technique and control Lyapunov function method, a robust adaptive controller is designed to complete the globally adaptive stability of the closed-lo...

In this paper, robust adaptive neural network control is investigated for a class of multi-input-multi-output (MIMO) pure-feedback nonlinear system with unknown nonlinearities. The unknown nonlinearities could be come from unmodeled dynamics, modeling errors, or nonlinear time-varying uncertainties. Based on the backstepping design technique and the universal approximation property of the neura...