Researchers at the University of California, Los Angeles (UCLA) have developed an optical computing framework that performs large-scale nonlinear computations using linear materials. Reported in ...

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 ...

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 ...

The NLP procedure (NonLinear Programming) offers a set of optimization techniques for minimizing or maximizing a continuous nonlinear function f(x) of n decision variables, x = (x 1, ... ,x n) T with ...

It appears that no particular approximate [nonlinear] filter is consistently better than any other, though . . . any nonlinear filter is better than a strictly linear one. 1 The Kalman filter is a ...

A prolific author of technical articles and books, Christophe P. Basso (ON Semiconductor, Toulouse, France) has written a new book, Linear Circuit Transfer Functions—An Introduction to Fast Analytical ...

Figure | Artistic depiction of a diffractive optical processor for massively parallel and universal approximation of nonlinear functions. Input variables are encoded into the phase of a light wave, ...