A new technical paper titled “Massively parallel and universal approximation of nonlinear functions using diffractive ...
UCLA researchers demonstrate diffractive optical processors as universal nonlinear function approximators using linear ...
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Optical system uses diffractive processors to achieve large-scale nonlinear computation
Researchers at the University of California, Los Angeles (UCLA) have developed an optical computing framework that performs ...
Adam Hayes, Ph.D., CFA, is a financial writer with 15+ years Wall Street experience as a derivatives trader. Besides his extensive derivative trading expertise, Adam is an expert in economics and ...
Abstract: Discusses various issues related to linguistic modeling of nonlinear functions with many input variables. Our task is to extract a small number of comprehensible linguistic rules from ...
Researchers have created a prediction method that comes startlingly close to real-world results. It works by aiming for ...
Reliable fault diagnostics in gearboxes is of great importance to industries to improve production quality and reduce maintenance costs. In this paper, an improved evolving fuzzy (iEF) technique is ...
Abstract: The deviation settlement mechanism (DSM) scheme enforces strict regulations on microgrid operators to comply with generation commitment norms set by grid operators. These norms are essential ...
We show that, compared with surgeon predictions and existing risk-prediction tools, our machine-learning model can enhance ...
Forty-five genes that encode kinesin superfamily proteins (also known as KIFs) have been discovered in the mouse and human genomes. KIFs are molecular motors that directionally transport various ...
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