2D adaptive residual subsampling for Radial Basis Functions: predictor(xx,x,u,lambda,c) - File Exchange

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Highlights from
2D adaptive residual subsampling for Radial Basis Functions

Jburgers(t,u,epsilon,Dx,Dy,Dx... Jacobian of 2D Burgers' Equation
burgers(t,u,epsilon,Dx,Dy,Dxx... 2D Burgers' Equation
coarserefine2d(f,intrv,theta,... 2-D adaptive residual subsampling method for radial basis function
dorefine2d(ibox,select,firstg... Box refinement process
ibox=initboxes2d(n,z) Initial coarse discretization on z x z
initcond(x,ctr,R) function for initial condition
mq2d(x,xc,c) 2-D multiquadric radial basis function
predictor(xx,x,u,lambda,c) Use RBF to interpolate values at new set points
adaptburgers2d_mol.m
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from 2D adaptive residual subsampling for Radial Basis Functions by Alfa Heryudono
This program solves initial-boundary value problems particularly 2D Burgers' equation adaptively

predictor(xx,x,u,lambda,c)

function uu = predictor(xx,x,u,lambda,c)
% Use RBF to interpolate values at new set points

N = length(x);
Nxx = length(xx);
B = zeros(Nxx,N);
for j=1:N
    B(:,j) = mq2d(xx,x(j,:),c(j));
end
uu = B*(lambda*u);

Highlights from 2D adaptive residual subsampling for Radial Basis Functions

Highlights from
2D adaptive residual subsampling for Radial Basis Functions