Multi-domain adaptive filtering by feasibility splitting

We propose multi-domain adaptive filtering based on the idea of feasibility splitting — dealing with feasibility in individual domains. The proposed approach provides a useful and mathematically rigorous framework to incorporate multiple pieces of information (expressed in different domains) efficiently. Indeed, it processes such multiple pieces of information by means of the metric projection in each individual domain; this is a significant advantage over existing single-domain approaches. Also we provide a reasonable strategy to treat the case where the available prior information is inconsistent. A convergence analysis and numerical examples are presented to support the proposed method.