I. Wavelet calculations.
 II. Calculation of approximation spaces in one dimension.
 III. Calculation of approximation spaces in one dimension II.
 IV. One dimensional problems.
 1 Decomposition of payoff function in one dimension. Adaptive multiscaled approximation.
 2 Constructing wavelet basis with Dirichlet boundary conditions.
 3 Accelerated calculation of Gram matrix.
 4 Adapting wavelet basis to arbitrary interval.
 5 Solving one dimensional elliptic PDEs.
 6 Discontinuous Galerkin technique II.
 7 Solving one dimensional Black PDE.
 8 Solving one dimensional mean reverting equation.
 A. Reduction to system of linear algebraic equations for mean reverting equation.
 B. Evaluating matrix R.
 C. Localization for mean reverting equation.
 D. Implementation for mean reverting equation.
 V. Stochastic optimization in one dimension.
 VI. Scalar product in N-dimensions.
 VII. Wavelet transform of payoff function in N-dimensions.
 VIII. Solving N-dimensional PDEs.

## Localization for mean reverting equation. imilarly to the section ( Localization ), we are going to calculate the interval .

In the section ( Mean reverting equation ) we calculated that the SDE may be integrated into We continue The integrals evaluate  for a standard normal random variable . We put the results together: (Mean reverting solution)
where we introduced the convenience notations and , , Based on a precision , , we would like to find two numbers and such that We calculate  Let be a number s.t. then and The process is connected to of the section ( Solving one dimensional mean reverting equation ) by the relationship (Exponential change) We aim to set the interval according to However, we still need to make two more modifications:

1. We need to adapt to the binary structure of our mesh. Similar argument was already made in the section ( Localization ).

2. We want to make time independent for smaller difference .

To achieve the goal 2 we set  We choose conservatively wider to preserve precision. Adaptive basis selection is a compensating procedure that preserves efficiency.

For the goal 1, we choose a scale parameter and Summary

(Localization for mean reverting equation summary) In context of the problem ( Strong mean reverting problem 2 ) we calculate the interval according to the following procedure.

Choose an integer scale parameter and a precision , and initial value .

Let be a number s.t. for standard normal variable .

Calculate where  Then The following is a consequence of the formulas ( Mean reverting solution ) and ( Exponential change ): (Analytical solution for mean reverting equation) 