English

The resolvent average of monotone operators: dominant and recessive properties

Optimization and Control 2015-05-12 v1 Functional Analysis

Abstract

Within convex analysis, a rich theory with various applications has been evolving since the proximal average of convex functions was first introduced over a decade ago. When one considers the subdifferential of the proximal average, a natural averaging operation of the subdifferentials of the averaged functions emerges. In the present paper we extend the reach of this averaging operation to the framework of monotone operator theory in Hilbert spaces, transforming it into the resolvent average. The theory of resolvent averages contains many desirable properties. In particular, we study a detailed list of properties of monotone operators and classify them as dominant or recessive with respect to the resolvent average. As a consequence, we recover a significant part of the theory of proximal averages. Furthermore, we shed new light on the proximal average and present novel results and desirable properties the proximal average possesses which have not been previously available.

Keywords

Cite

@article{arxiv.1505.02718,
  title  = {The resolvent average of monotone operators: dominant and recessive properties},
  author = {Sedi Bartz and Heinz H. Bauschke and Sarah M. Moffat and Xianfu Wang},
  journal= {arXiv preprint arXiv:1505.02718},
  year   = {2015}
}