What are features in signal processing using a more tangible or less abstract description
A feature is a number that describes one aspect of a signal.
Signals can be very complex, and the simplest analysis tools (like a time plot, a spectrum, or an energy measurement) don't tell you everything; in fact, for specific types of analyses, they almost don't tell you anything useful.
So, features are designed to describe very specific aspects of a signal.
To make an analogy, let's say you're an expert in ice cream and want to compare two brands. Just looking at a picture or the list of ingredients is not enough. You can taste them, but you can't accurately describe the taste to your colleagues (just like you can listen to sound but you can't describe exactly what it sounds like).
So, you come up with &quot;features&quot; about the ice cream: the density, the statistics of the nitrogen bubbles inside it, the sugar/fat ratio, the crystalinity, whatever. Some of the features will be useless, but some will turn out to be really good at objectively conveying something interesting about ice cream.