chebyshev differentiation matrix in matlab

```main.m```% define grid points
N = 50; % number of grid points
x = cos(pi*(0:N)/N); % Chebyshev-Gauss-Lobatto nodes

% calculate differentiation matrix
D = zeros(N+1,N+1);
for i=1:N+1
for j=1:N+1
if i~=j
D(i,j) = ((-1)^(i+j))/(x(i)-x(j));
end
end
end
D = D - diag(sum(D'));

% apply differentiation matrix to a function
f = @(x) exp(cos(x)); % define function
df = D*f(x'); % differentiate f at grid points
```424 chars19 lines```

Initialize parameters such as the number of grid points `N` and define the Chebyshev-Gauss-Lobatto nodes `x`. Then, calculate the differentiation matrix `D` using a nested `for` loop that applies the Chebyshev differentiation formula to each pair of grid points. Finally, apply the differentiation matrix `D` to a function `f(x)` and store the result in `df`. The result is a vector of derivatives, one for each grid point. This method is based on spectral methods, which can achieve very high accuracy with fewer grid points compared to finite difference methods.

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