Feature transformation and J-function

The feature transformation is the same as (5.1) in Section 5.1:

 (6.1)

but the similarity ends here. Because is limited to a compact set, the unit hypercube , an energy statistic is theoretically not needed for MEPP (See Theorem 2 in Section 3.2.1) 6.1Whereas the exponential distribution played a central role in the analysis of the singly-bounded case, the mutivariate truncated exponential distributon (TED) plays an important role in the unit hypercube (all elements of in ). The uniform reference distribution, results in maximum entropy (See Theorem 2 in Section 3.2.1), and is a special case of the mutivariate TED. When , the J-function simplifies to

So, computing the J-function is primarily a task of computing , which can be done using two methods as described in Section 16.7. The J-function is implemented by software/module_A_dbound.m, and tested by software/module_A_dbound_test.m. The re-synthesis approach using UMS is described in Secion 6.2 and implemented by software/module_A_dbound_synth.m.

Baggenstoss 2017-05-19