Design of risk-sensitive optimal control for stochastic recurrent neural networks by using Hamilton-Jacobi-Bellman equation

Keyphrases

• Hamilton-Jacobi-Bellman Equation 100%
• Stochastic Recurrent Neural Networks 100%
• Risk Control 100%
• Risk-sensitive 100%
• Optimality Criteria 50%
• Numerical Examples 50%
• Lyapunov Methods 50%
• Inverse Optimality 50%
• Theoretical Design 50%
• Parameter Sensitivity 50%
• Risk Sensitivity 50%
• State Feedback Controller 50%

Mathematics

• Stochastics 100%
• Neural Network 100%
• Optimal Control Theory 100%
• Bellman Equation 100%
• Optimality 50%
• Optimality Criterion 50%
• Numerical Example 50%

Computer Science

• Recurrent Neural Network 100%
• Numerical Example 50%
• Sensitivity Parameter 50%
• state-feedback controller 50%
• Risk Sensitivity 50%