Learn about some common nonlinear regression functions and how to use Excel tools and techniques to fit them to your data.

Lookup tables and Taylor series are two common methods for interpolating between experimentally gathered data or for generating a known function such as a ...

This research introduces an approach to functional Magnetic Resonance Imaging (fMRI) analysis, focusing on Nonlinear Functional Connectivity (NFC). Traditional linear correlation methods in fMRI ...

Often with data from immunoassays, the concentration-response relationship is nonlinear and intra-assay response variance is heterogeneous. Estimation of the standard curve is usually based on a ...

Specifically, a nonlinear weighted graph convolution network (NWGCN) module is designed, which utilizes a graph-in-graph structure based on cosine similarity-based normalized weighted graph ...

This paper presents an asymptotic approximation for the marginal density of a nonlinear function g (θ) that is applicable when the joint density of θ is dominated by a single mode and the Jacobian of ...

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 ...