[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).

This valuable study presents a technically sophisticated intravital two-photon calcium imaging approach to characterize Ca²⁺ dynamics in distinct populations of meningeal macrophages in awake, freely ...

Abstract: Polynomial multiplication is the basic and most computationally intensive operation in ring-learning with errors (ring-LWE) encryption and "somewhat" homomorphic encryption (SHE) ...

Abstract: This article presents a novel path-following-method-based polynomial fuzzy control design. By examining the stabilization problem, the nonconvex stabilization criterion represented in terms ...

Matlab runs extremely well on the new Apple Silicon Macs, but if you want the best possible performance from these new processors, the real number-crunching power is on their onboard GPU cores. This ...