Finite-time zeroing neural networks with novel activation function and variable parameter for solving time-varying Lyapunov tensor equation.
Zhaohui QiYingqiang NingLin XiaoJiajie LuoXiaopeng LiPublished in: Appl. Math. Comput. (2023)
Keyphrases
- activation function
- neural network
- global exponential stability
- hidden layer
- feed forward neural networks
- artificial neural networks
- back propagation
- feed forward
- neural nets
- hidden neurons
- multilayer perceptron
- learning rate
- feedforward neural networks
- nonlinear functions
- radial basis function
- backpropagation algorithm
- hidden nodes
- single layer
- recurrent neural networks
- basis functions
- chaotic neural network
- dynamical systems
- lyapunov function
- sufficient conditions
- multi layer perceptron
- rbf neural network
- pattern recognition
- training phase
- sigmoid function
- nonlinear systems
- fuzzy neural network
- multi layer
- differential equations
- closed loop
- fuzzy logic
- control law
- network architecture
- control scheme
- convergence rate
- extreme learning machine
- membership functions
- mathematical model
- expert systems
- support vector
- machine learning