Decoding Geometric Properties in Non-Random Data from First Information-Theoretic Principles

arXiv:2405.07803v1 Announce Type: cross
Abstract: Based on the principles of information theory, measure theory, and theoretical computer science, we introduce a univariate signal deconvolution method with a wide range of applications to coding theory, particularly in zero-knowledge one-way communication channels, such as in deciphering messages from unknown generating sources about which no prior knowledge is available and to which no return message can be sent. Our multidimensional space reconstruction method from an arbitrary received signal is proven to be agnostic …

applications arxiv coding communication computer computer science cs.cl cs.cr cs.ir cs.it data decoding information knowledge math.it math.st measure messages non principles random science signal stat.th theory