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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.

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  1. Linear algebra
  2. Algebra
  3. Fields of mathematics
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