Adaptive Software Defined Radio Detection With Artificial Intelligence
Distinguishing between different types of audio signals is a common, yet complex computational challenge. In many cases, accurate discrimination between different types of audio signals is essential to the function of many electronic devices. Traditional Digital Signal Processing (DSP) techniques for determining a signal's audio class require careful calibration by the design engineer. However, by combining traditional DSP techniques with modern Software Defined Radio (SDR) methods, the design engineer can create a more flexible, adaptive system. This paper proposed an artificial intelligence model to create a highly flexible, yet accurate discrimination engine on an SDR platform.