  This paper delves into the analysis of nonlinear deformation induced by
dielectric actuation in pre-stressed ideal dielectric elastomers. It formulates
a nonlinear ordinary differential equation governing this deformation based on
the hyperelastic model under dielectric stress. Through numerical integration
and neural network approximations, the relationship between voltage and stretch
is established. Neural networks are employed to approximate solutions for
voltage-to-stretch and stretch-to-voltage transformations obtained via an
explicit Runge-Kutta method. The effectiveness of these approximations is
demonstrated by leveraging them for compensating nonlinearity through the
waveshaping of the input signal. The comparative analysis highlights the
superior accuracy of the approximated solutions over baseline methods,
resulting in minimized harmonic distortions when utilizing dielectric
elastomers as acoustic actuators. This study underscores the efficacy of the
proposed approach in mitigating nonlinearities and enhancing the performance of
dielectric elastomers in acoustic actuation applications.
