The Study On Modulation Singnal Recognition Based On VPRS And RBF Neural Network Model

Communication signals'modulation recognition is an important part of received signals processed, whose basic tasks are analysis, distinguish and classify unknown signals. By identifying unknown signals, we can know more about signals'structure and properties, provide parameters for signals' demodulation and analysis, and obtain the content of useful information ultimately.This paper developes a prototype system of digital signals modulation recognition, which based on IFDIS'VPRS and RBF artificial neural network, with 2ASK,4ASK,2FSK,4FSK,2PSK,4PSK digital modulation signals as the main discuss object, with rough set theory and artificial neural network theory as the main tools. The primary contributions are as follows:1. The paper introduces the VPRSM into incomplete fuzzy information system, and extends the rough set theory of the IIS, which made the classic RS theory possess more general meaning;2. The paper discusses signal modulation recognition of radial basis function neural network (RBF) and analysis the particularity; 3. The paper researches on signal modulation recognition of combining with VPRS and RBF, puts forward a feasible model and precision reduction algorithm, do some work on improving class-precision in rough set and generalization capability.