Overcompleteness

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Overcompleteness is a concept from linear algebra that is widely used in mathematics, computer science, engineering, and statistics (usually in the form of overcomplete frames). It was introduced by R. J. Duffin and A. C. Schaeffer in 1952.^[1]

Formally, a subset of the vectors ${\displaystyle \{\phi _{i}\}_{i\in J}}$ of a Banach space ${\displaystyle X}$, sometimes called a "system", is complete if every element in ${\displaystyle X}$ can be approximated arbitrarily well in norm by finite linear combinations of elements in ${\displaystyle \{\phi _{i}\}_{i\in J}}$.^[2] A system is called overcomplete if it contains more vectors than necessary to be complete, i.e., there exist ${\displaystyle \phi _{j}\in \{\phi _{i}\}_{i\in J}}$ that can be removed from the system such that ${\displaystyle \{\phi _{i}\}_{i\in J}\setminus \{\phi _{j}\}}$ remains complete. In research areas such as signal processing and function approximation, overcompleteness can help researchers to achieve a more stable, more robust, or more compact decomposition than using a basis.^[3]