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symmetric matrix concept

DefinitionA square matrix equal to its own transpose. Its eigenvalues are real, its eigenvectors can be chosen orthonormal, and it is the sum of its eigenvalues times the outer products of its eigenvectors. Almost every matrix in the book is one. Primer L, equation L.14. Also symmetric.
ExampleThe matrix with rows (2, 1) and (1, 2) is symmetric, and the one with rows (2, 1) and (0, 2) is not.
BookData Mining as Observation, draft 0.2, commit f3914f0; entry id symmetric-matrix, kind concept.
Statusno ledger row names this entry. Corrections: none recorded.
Defining equation

Book equation L.14.

Assumptions and scopenone
Prior artnone recorded
Evidencenone
Reviewedsemantic review 2026-09-09; generated 2026-09-10 from records at the commits on the provenance page.

Equation

Book equation L.14.

\[A=\sum_{i=1}^{d}\lambda_i\,v_iv_i^{\top}=V\Lambda V^{\top},\qquad V^{\top}V=I,\qquad \Lambda=\operatorname{diag}(\lambda_1,\dots,\lambda_d).\]

Conditions

none

Ledger

none

First stated

Primer L section L.3 of Data Mining as Observation, added in draft 0.3 (2026-09-09) for the ECE 514 readers whose first courses are far behind. The idea is standard and TSK Appendix A covers it at length.

Measurements

none

Failures and corrections

none

Invariance envelope

none declared

Machine checked

none

Used in

Data Mining as Observation primers L and S, chapters 0, 3, 4, 5, 9, 10.

Related

transpose; eigenvalue, eigenvector; spectral decomposition; covariance matrix.

See also

none

Status

Generated 2026-09-10 by encyclopedia/generate.py; book at observation-data-mining f3914f0; the commit of every record is listed in the encyclopedia’s provenance.

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