A Novel Approximation Algorithm Based on Genetic Programming in Digital Learning Environment

With the development of information and the integration of media, it has great practical significance and research value to build a digital learning environment based on the complicated electronic circuit. However, the complicated electronic circuit in real-time need a complex and expensive technology. In order to overcome the high cost and technology, an approach was proposed for simplifying generation by approximating the excitations with rectangular pulses, triangular pulses and cosine waves which can be implemented with a moderate cost in analogical electronics. In this work, we improved a novel approach based on genetic programming, The differences between theoretical excitation signals and the approximation driving pulses, related to their excitation effects, were minimized by genetic programming. From these results, the accuracy of simulation can be improved by the new approach, the difference between theoretical complicated digital signals and the new approach is reduced. A trade off is obtained between the costs of implementation of digital processing in digital learning environments.