GitHub

Fits linear and polynomial models to data using linear least squares and approximates nonlinear models through linearization.

[c,r2,eqn] = lsqcurvefit_approx(x,y) returns the model coefficient vector c = [m,b] for the linear fit to a data set defined by the vectors x (independent variable) and y (dependent variable).
Quanta Magazine

Long-Sought Proof Tames Some of Math’s Unruliest Equations

Mathematicians finally understand the behavior of an important class of differential equations that describe everything from ...
GitHub

zwicker-group/py-pde

py-pde is a Python package for solving partial differential equations (PDEs). The package provides classes for grids on which scalar and tensor fields can be defined. The associated differential ...
IEEE

Solving Future Different-Layer Nonlinear and Linear Equation System Using New Eight-Node DZNN Model

Abstract: In this article, a future different-layer nonlinear and linear equation system (DLNLES) is investigated. First, based on a zeroing neural network (ZNN) method, a zeroing equivalency theorem ...
IEEE

A Predefined-Time Adaptive Zeroing Neural Network for Solving Time-Varying Linear Equations and Its Application to UR5 Robot

Abstract: Time-varying linear equations (TVLEs) play a fundamental role in the engineering field and are of great practical value. Existing methods for the TVLE still have issues with long computation ...