Finding Linearly Generated Subsequences

We develop a new algorithm to compute determinants of all possible Hankel matrices made up from given finite length sequence over field. Our fits within the dynamic programming paradigm by exploiting recursive relations on together with observations concerning distribution zero among matrix sizes allowed original sequence. The can be used isolate \emph{very} efficiently linear shift feedback registers hidden in strings random prefix and postfix for instance and, therefore, recovering shortest generating vector. mathematical identities also any other situations involving matrices. implement parallel version our algorithm. compare results empirically trivial which consists computing each accelerated approach single processor is faster than 160 processors input sequences 16384 instance.