The complex-valued encoding for dicision-making based on aliasing data

Decision-making in the control of complex systems is based on the analysis of multidimensional data. These data need to recognize them and establish functional dependences. The search for effective methods to the pattern recognition is continued. An essential step in the development of the effective methods of encoding is to create recognition systems, using sparse coding and self-learning [1]. We propose a multi-valued mapping, which improves the possibility of image classification and parameterization data for decision-making for complex multidimensional data.