Analytics: Finding hidden truths using Signal Extraction
We are guided by methods for extracting digital signals which have been presented in a noisy, high-dimensioned space. A substantial literature has developed around signals carried on MW and RF carriers, including CDMA, military applications and WI-FI. Equally, there is a mature literature on econometric and commercial applications, including UHFT (ultra-high frequency trading), trend determination and limited perspective financial modelling.
Often, the SNR is so low that the signal falls below the statistically significant level, and our goal is to apply iterative techniques for detection and rectification to extract the signal, then validate it by independent tests. This is a highly active area in current research, and promises excellent outcomes.
Our work will involve the implementation of methods evolving in the literature, with a particular emphasis on detecting trends in sub-major characteristic modes to inform models of commercial systems.