青云翻译

Can neural network to learn the unknown nonlinear function approximation capability of the above inverse system combine to construct the inverse system function to achieve the decoupling of the linearization of the nonlinear discrete system does not meet the conditions.

Neural network learning for unknown nonlinear function approximation ability and combined with the inverse of the above systems, building inverse functions to achieve the does not satisfy the conditions of linearization and decoupling of nonlinear discrete-time systems.

May and approaches the neural network to the unknown nonlinear function study ability to unify with the above counter system, the structure counter system function realizes to does not satisfy the condition non-linearity to be separated the system the linearized decoupling.

The neural network for the unknown non-linear function of learning and approach with more capacity of the inverse system with reverse-system, the constructor function to achieve the conditions are not met non-linear discrete systems of linear uncoupled.

Neural network learning for unknown nonlinear function approximation ability and combined with the inverse of the above systems, building inverse functions to achieve the does not satisfy the conditions of linearization and decoupling of nonlinear discrete-time systems.