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Properties of the Transpose
The transpose interacts cleanly with all the matrix operations we have studied. Addition and scalar multiplication pass straight through: and . For products, the rule reverses order: .
When is invertible, so is , and its inverse is the transpose of : . This is sometimes written . You can verify it directly: .
A useful extension of the product rule: . Each factor transposes and the whole product reverses. This generalizes to any number of factors.
Formal View
Theorem 5.2 — Transpose Algebra
Let and be matrices, , and let have a well-defined product . Then:\begin{enumerate} \item \item \item \item \item If is square and invertible: \end{enumerate}
Why This Matters
These algebraic rules make the transpose a well-behaved operation that fits seamlessly into calculations.
- The rule is used constantly in deriving gradient formulas in machine learning
- In numerical linear algebra, computing (the pseudoinverse) relies on all these identities
- When checking if a matrix is symmetric, the identity immediately shows is always symmetric
Quiz
Question 1
Which of the following is always symmetric (equals its own transpose) for any matrix ?
Question 2
If is invertible, then .
Common Mistakes
- Applying the transpose rule as — always reverse the order: .
- Assuming every matrix plus its transpose equals the zero matrix — is symmetric, not zero.