Statistical spectral analysis: a nonprobabilistic theory

Part I of the book reformulates the entire problem of statistical spectral analysis in terms of time averages instead of the traditional but more abstract ensemble averages.Part II builds on this theory and methodology by extending and generalizing it from statistically stationary data to cyclostationary data. Dr. Nelson Blachman, well known communication systems author, writes:
My interest in Dr. Gardner's research is concerned with the advances in cyclostationary signal processing that has been his greatest contribution to electrical engineering research. In fact, Professor Gardner is "Mr. Cyclostationary", the promoter and leading international researcher in this important signal processing area, with two textbooks, numerous papers, and a federal government subsidized workshop to his credit. As a scientist involved with Department of Defense signal processing research aimed at threat analysis of signals related to national security interests, I can indicate to you that Dr. Gardner's work has had profound impact on the analysis of these signals, but classification of the analysis has kept the importance of his work from being known to the general public and others in academia. There is another attribute of Dr. Gardner's research and tutorial material that makes him stand out among so many of my other academic colleagues, and that is his depth of research (especially historical and mathematical detail) and his attention to precision and detail in his writings. I have always found it difficult to find errors and to take issue with any of Professor Gardner's papers because he has meticulously done his research; this is in contrast to so many other academics who tend to be more sloppy in their mathematical precision and who do not always thoroughly check the technical literature in depth. I believe this high degree of professional research has contributed greatly to the widespread acceptance of Dr. Gardner's technical writings as being the preeminent authority on cyclostationary signal processes and their exploitation.