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I. Wavelet calculations.
II. Calculation of approximation spaces in one dimension.
III. Calculation of approximation spaces in one dimension II.
IV. One dimensional problems.
V. Stochastic optimization in one dimension.
VI. Scalar product in N-dimensions.
1. Two-sided area of integration, positive a.
A. Calculation of w1 for positive a.
B. Calculation of w2 for positive a.
C. Calculation of w3 for positive a.
2. Two-sided area of integration, negative a.
3. Indexing integration domains.
4. Summary. Calculation of scalar product in N dimensions.
5. Indexing integration domains II.
6. Scalar product in N-dimensions. Test case 1.
7. Scalar product in N-dimensions. Test case 2.
8. Scalar product in N-dimensions. Test case 3.
9. Implementation of scalar product in N-dimensions.
VII. Wavelet transform of payoff function in N-dimensions.
VIII. Solving N-dimensional PDEs.
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Two-sided area of integration, positive a.


e continue derivations of the previous section for the area of integration MATH . We introduce the following convenience notation: MATH If $c_{-}<c_{+}$ and $a_{n-1}>0$ then MATH . We calculate for $a_{n-1}>0$ , $c_{-}<c_{+}$ : MATH Let MATH then MATH There are six possibilities of how two intervals might locate relatively to each other: MATH We consider each possibility and express it in terms of at most two-sided inequality for MATH : MATH MATH MATH MATH MATH MATH We now express the value of MATH for each of these six cases: MATH for some numbers MATH , $C_{n-1}$ . We arrive to the following recursive representation: MATH MATH MATH MATH MATH

The recursion ends with $n=1$ : MATH where one of the numbers $c_{-}$ , $c_{+}$ may be $\pm\infty$ .

It remains to calculate the numbers MATH .




A. Calculation of w1 for positive a.
B. Calculation of w2 for positive a.
C. Calculation of w3 for positive a.

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