Graphics Programs Reference
In-Depth Information
functionr=residual(u) %Boundaryresidual.
global XSTART XSTOP H
x = XSTART;
[xSol,ySol] = runKut4(@dEqs,x,inCond(u),XSTOP,H);
r = ySol(size(ySol,1),1) - 1;
Here is the solution:
>>
x
y1
y2
0.0000e+000
0.0000e+000
1.5145e+000
2.0000e-001
2.9404e-001
1.3848e+000
4.0000e-001
5.4170e-001
1.0743e+000
6.0000e-001
7.2187e-001
7.3287e-001
8.0000e-001
8.3944e-001
4.5752e-001
1.0000e+000
9.1082e-001
2.7013e-001
1.2000e+000
9.5227e-001
1.5429e-001
1.4000e+000
9.7572e-001
8.6471e-002
1.6000e+000
9.8880e-001
4.7948e-002
1.8000e+000
9.9602e-001
2.6430e-002
2.0000e+000
1.0000e+000
1.4522e-002
Note that y (0)
=
1
.
5145,sothatour initial guesses of 1.0 and 2.0 wereon the
mark.
EXAMPLE 8.2
Numerical integration of the initial value problem
y +
y (0)
=
=
=
4 y
4 x
y (0)
0
0
yielded y (2)
653 64. Use this information to determine the valueof y (0) that
wouldresult in y (2)
=
1
.
=
0.
Solution We use linear interpolation
u 2
u 1
u
=
u 2 θ
( u 2 )
θ
( u 2 )
θ
( u 1 )
y (0) and
y (2).Sofar we are given u 1 =
where in our case u
=
θ
( u )
=
0 and
θ
( u 1 )
=
1
653 64. To obtain the second point, we needanother solution of the initial value
problem. An obvious solutionis y
.
0 and y (0)
y (2)
=
x , which gives us y (0)
=
=
=
1.
Thus the second point is u 2 =
θ
=
1 and
( u 2 )
1. Linear interpolationnowyields
1
0
y (0)
=
=
653 64 =
.
u
1
(1)
2
529 89
1
1
.
Since the problemislinear, nofurtheriterations are needed.
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