A Deterministic Study of Delta Modulation (DM) using Machine Learning Approach

This paper primarily focuses on the generation of transmission code by Delta Modulation (DM) using Machine Learning Algorithm. Here, models like Logistic Regression and Support Vector Classification have been applied separately on both Sinusoidal and Triangular waves. The outputs have been analysed and compared with that of the default theoretical output and also with the outputs generated by an already existing method. Additionally, we have examined the yield of Matlab and Machine learning both. Finally, the efficiency of the process is measured in case of both the waveforms.