A new LMU study shows how proteins function reliably even without a stable 3D structure—and the crucial importance not only of short sequence motifs, but also of chemical characteristics. Many ...

Abstract: This article investigates the bipartite consensus problem for nonlinear networked systems with cooperative–competitive interactions subject to the nonlinear control protocols. Based on ...

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 ...

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 ...

Abstract: This paper studies the distributed optimization problem of high-order multi-agent systems with unknown nonlinear terms and input saturation. Unlike existing results, nonlinear functions in ...

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 ...

Current methods for predicting missing values in datasets often rely on simplistic approaches such as taking median value of attributes, limiting their applicability. Real-world observations can be ...