Signal Processing

The machines we build include signals carrying information and energy of a variety of forms: sensor inputs, control signals, power outputs. This can be extended arbitrarily into feedback control systems, generative performance algorithms, machine learning, and much more. The commonality is that signals carry information about temporal and spatial processses that once digitized can be manipulated computationally.

This course can’t begin to address the full scope of techniques, but can provide some basic tools for extending our physical system data into computational processes.