Using the optimized radial basis function neural network and instantanous features for ARCS

Automatic recognition of the communication signals (ARCS)plays an important role for various applications, this paper presents a hybrid intelligent system that automatically recognizes a variety of digital communication signals. The hybrid system includes three main modules: feature extraction module, classifier module and optimization module. In the feature extraction module, we have used the balanced combination of the instantaneous features and other features of the signals. In the classifier module, a radial basis function neural network is proposed as the classifier. In the optimization module it is optimized the recognizer design by genetic algorithm for selection the best structure of the classifier. Simulation results show that the proposed technique has very high recognition accuracy even at very low SNRs.