핵심 개념
RNN Reservoir Systems exhibit uniform strong universality for approximating a family of functions.
초록
Introduction to the study of the universality of RNN Reservoir Systems.
Preliminaries on dynamical systems and reservoir systems.
Approximation bounds of feedforward neural networks with ReLU and sigmoid activation functions.
Weak universality of RNN Reservoir Systems for finite-length inputs.
Internal approximation by RNN Reservoir Systems.
Proof of weak universality.
Overview of uniform strong universality for finite-length inputs.
통계
임의의 양수에 대해, 어떤 클래스의 함수를 근사하는 충분히 큰 RNN Reservoir 시스템을 구성할 수 있다.
근사 오차는 양수에 의해 상한이 정해진다.
RNN Reservoir 시스템은 FNN 근사 오차의 상한을 결정하는 데 사용된다.
인용구
"RNN Reservoir Systems exhibit uniform strong universality for approximating a family of functions."