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This paper provides an extended analysis of the adaptive digital predistortion technique initially proposed and conceptually overviewed in . This digital predistortion technique is suitable for wideband high crest factor applications (digital audio broadcasting, digital video broadcasting-terrestrial & wideband code division multiple access high power transmitters) and overcomes the technical deficiencies of the traditional direct learning method. Specifically, predistortion filter parameter estimation is modeled as a generic mathematical optimization problem instead of a linear regression problem. In addition, the optimization objective is derived in the frequency instead of the time domain. A hybridly pruned Volterra series with memory is used to implement the predistortion filter. Hybrid pruning leads to a small optimization vector space, whilst the predistortion filter memory makes the method well suited to wideband applications. Given that predistortion filter parameter estimation does not rely on known test signals being injected into the transmitter, the method is on-air adaptive. Implementation aspects of the technique not covered in , but requiring extended coverage in this paper, include selection of mathematical optimization algorithms, predistortion filter memory estimation, weighted adjacent channel power weighting function application, and on-air adaption performance. Results obtained from actual hardware are presented.