Abstract
A method is presented for identifying signal space generated in decentralized decision systems. The decision process is assumed to be embedded in information intensive environment so that signals are generated via sustainable nonlinear dynamics. For the class of square summable nonlinear signals a universal dynamics is designed for scanning signal space without explicit reference to decision mechanisms nor nonlinear dynamics. Obtained dynamics is shown to be enough chaotic for the description of signal filter to cover the complex image of signal space. The validity and efficiency of scanning scheme are demonstrated via simulation studies.
