In this third lesson on fundamental signal processing concepts you will learn about the role of mathematical models in signal processing. Models are used to describe characteristics of signals and or noise that are relevant to the information of interest in the signal. Mathematical models underlie all algorithms in signal processing, including separation of signals and noise, signal compression, and estimation of signal parameters.
Systematic approaches to signal processing algorithm design and performance analysis are possible because of the reliance on mathematical models. Understanding this concept will further develop your foundation and set the context for your further studies of signal-processing algorithms.
Key Concepts and Transcript
Concepts and Transcript for Models, Math, and Real-World Signals
