Signal processing is a field devoted to the extraction of information from signals, both analog and digital. In this course, we will focus on the analysis and development of digital signal processing algorithms. These algorithms are typically implemented in software on general purpose computing devices, though there is no reason many of these algorithms cannot be implemented in special purpose hardware.

Adaptive systems are devices that adjust themselves to an ever-changing environment. Often the goal is to improve performance through continuous interaction with its surrounding environment. Adaptive signal processing deals with the design of such systems for signal processing applications. These systems are often based on statistical methods. Important considerations include off-line vs. online adaptation, supervised vs. unsupervised, and feedforward vs. feedback control. Machine learning today plays an integral role in adaptive signal processing applications.