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Numerical Integration 59<br />

(3.8.14) pw =<br />

<br />

p 2 w,n − 1<br />

2π<br />

2<br />

[(p,Tn)w,n]<br />

1<br />

2<br />

, ∀p ∈ Pn,<br />

when specialized to the Legendre and Chebyshev cases respectively.<br />

The result of theorem 3.8.3 can be generalized as follows:<br />

(3.8.15) (p,q)w = (p,q)w,n − un 2 w,n − un 2 w<br />

un 4 w,n<br />

We leave the proof as exercise.<br />

(p,un)w,n (q,un)w,n, ∀p,q ∈ Pn.<br />

Another quant<strong>it</strong>y we would like to compute is the integral 1<br />

−1 p2 dx, in terms of<br />

the values of p ∈ Pn at some nodes. When the nodes are the Legendre Gauss-Lobatto<br />

points, we can use (3.8.13). On the contrary, we are in a s<strong>it</strong>uation similar to that of<br />

section 3.7. We only solve the problem for Chebyshev Gauss-Lobatto nodes. Here we<br />

have p 2 ∈ P2n, while (3.7.1) is satisfied only in Pn. The idea is to duplicate the number<br />

of points and still use (3.7.1). Recalling (3.1.11) and (3.1.4), in the Chebyshev case we<br />

have the remarkable result that<br />

(3.8.16) {ξ (n)<br />

i }1≤i≤n ∪ {η (n)<br />

j }0≤j≤n = {η (2n)<br />

k }0≤k≤2n.<br />

Since p is known at the points (3.1.11) and p(η (n)<br />

j ) = p(η (2n)<br />

2j ), 0 ≤ j ≤ n, we can<br />

extrapolate <strong>it</strong>s value at the points (3.1.4) w<strong>it</strong>h the help of (3.2.7):<br />

n<br />

(3.8.17) p(η (2n)<br />

2i−1 ) = p(ξ(n) i ) =<br />

j=0<br />

Now, we can use (3.7.1), obtaining ∀p ∈ Pn<br />

(3.8.18)<br />

=<br />

n<br />

j=0<br />

1<br />

−1<br />

p 2 dx =<br />

p 2 (η (n)<br />

j ) χ (2n)<br />

2j +<br />

2n<br />

m=0<br />

n<br />

<br />

n<br />

i=1<br />

p(η (n)<br />

j ) ˜ l (n)<br />

j (ξ (n)<br />

i ), 1 ≤ i ≤ n.<br />

k=0<br />

p 2 (η (2n)<br />

m ) χ (2n)<br />

m<br />

p(η (n)<br />

k ) ˜ l (n)<br />

k (ξ(n)<br />

i )<br />

2<br />

χ (2n)<br />

2i−1 .<br />

Finally, the weights can be determined from (3.7.2), and the coefficients ˜ l (n)<br />

k (ξ(n)<br />

i )<br />

from (3.2.10) and (3.1.16). This procedure has a computational cost proportional to n 2 ,<br />

versus the cost of implementing (3.8.10), which is proportional to n.

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