What modest academic success I’ve had in the area of cyclostationary signal theory and cyclostationary signal processing is largely due to the patient mentorship of my doctoral adviser, William (Bill) Gardner, and the fact that I was able to build on an excellent foundation put in place by Gardner, his advisor Lewis Franks, and key Gardner students such as William (Bill) Brown.
For a long while, since 2015, the CSP Blog was the only website on the planet devoted entirely to cyclostationary signals and cyclostationary signal processing. No more! Gardner created a website in 2018 called cyclostationarity.com. Go check it out if you want a different perspective and emphasis relative to the CSP Blog.
I don’t think the two CSP websites will have a lot of duplicated material. The CSP Blog is intended for practioners of signal processing; it looks to me like cyclostationarity.com is aimed at providing accessible versions of theoretical concepts and results. That mirrors how I think of myself and Gardner–I am not his equal at theory, but I don’t think he directly programs computers or processes data.
It seems appropriate at this point to provide some historical foundational documents of CSP. These are documents that can be found on the internet, with a little effort, but I thought it would be nice to put them all on one page. The first is the book Signal Theory by Franks. It is a book on random processes, signal representation and analysis, and topics like signal detection. There is some cyclostationarity in there too.
The second is the doctoral dissertation of Gardner. This is of interest to serious scholarly researchers in the field, such as doctoral students who are plumbing the depths of the history of signal theory and cyclostationary signal processing.
The third is the doctoral dissertation of Brown. Key topics include detailed presentation of the fraction-of-time probability approach to signal analysis, periodically time-variant linear filtering for complex-valued signals, introduction of computationally efficient spectral correlation function estimators, and analysis of the variance (SNR) of the outputs of such estimators.
Comments are welcome.