A new technical paper titled “Massively parallel and universal approximation of nonlinear functions using diffractive processors” was published by researchers at UCLA. “Nonlinear computation is ...

A new switching-dependent prescribed performance adaptive control scheme gives switched nonlinear systems mode-specific ...

Nonlinear functions defined over finite fields lie at the heart of modern algebraic design, with wide-ranging influence from cryptography to coding theory. Such functions depart from linear or affine ...

Many systems obey simple, linear rules: If you pull twice as hard on a spring, it stretches twice as far. However, when we introduce very large forces or complicated interactions, that linear rule ...

Researchers have trained a two-hidden-layer neural network with Levenberg–Marquardt backpropagation to accurately approximate ...

Activation functions play a critical role in AI inference, helping to ferret out nonlinear behaviors in AI models. This makes them an integral part of any neural network, but nonlinear functions can ...