Overcompleteness is a term used in various fields, including mathematics, signal processing, statistics, and machine learning, to describe a situation where a system or representation contains more elements (parameters, basis functions, etc.) than are strictly necessary to describe the data or achieve a particular goal. ### Key Points about Overcompleteness: 1. **Redundant Representations**: In an overcomplete system, there are more degrees of freedom than required.
Articles by others on the same topic
There are currently no matching articles.