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Theorem 1 (Residue Theorem)Let fbe analytic in the region Gexcept for the isolated singularities a1,a2,…,am.If γis a closed rectifiable curve in Gwhich does not pass through any of the points akand if γ≈0in G,then
12πi∫γf=m∑k=1n(γ;ak)Res(f;ak).
1.1.1 this is a subsection
Here is some code in minipage
1%check if we converged or not 2if k>opt.MAX_ITER || gradientNormTol(k)<=opt.gradientNormTol ... 3|| (k>1 && levelSets(k)>levelSets(k−1))% check for getting worst 4 keepRunning = false; 5else 6 .... 7end
Here is example using listings
1%Evaluate J(u) at u 2function f = objectiveFunc(u) 3 u=u(:); 4 N = size(u,1); 5 f = 0; 6 for i = 1:N−1 7 f = f + 100*(u(i+1)−u(i)^2)^2 + (1−u(i))^2; 8 end 9end
2.1.2 Example on page 500, textbook (Edwards&Penny;, 3rd edition)
problem This problem was solved in textbook using matrix exponential. Here is solved using
the fundamental matrix only. Use the method of variation of parameters to solve
x'=Ax+f(t).
A=(423−1)ˉf(t)=(−154)te−2tˉx(0)=(73)
Solution
The homogeneous solution was found in the book as
ˉxh=c1(1−2)e−2t+c2(21)e5t
Following scalar case, the guess would be
ˉxp=(ˉb+āt)e−2t but since
e−2t is in the homogeneous, we
have to adjust to be ˉxp=(ˉbt+āt2)e−2t+ˉce5t. Notice
we had to add ˉce5t, else it will not
work if we just guessed ˉxp=(ˉbt+āt2)e−2t based
on what we would do in scalar case, we will find we get
ā=ˉb=0. This
seems to be a trial and error stage and one just have to try to find out. This is why
undermined coefficients for systems is not as easy to use as with scalar case.
Hence
ˉxp=(ˉbt+āt2)e−2t+ˉce5t
Now we plug-in this back into the ODE and solve for
ā,ˉb,ˉc.
But an easier method is to use Variation of parameters. The fundamental matrix
is