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- The 0 vector is unique.#23958
- The 0 vector multiplied by any scalar equals the 0 vector.#23961
- The additive inverse of a vector equals the vector multiplied by -1.#23963
- The additive inverse of a vector is called the negative of the vector.#23956
- The additive inverse of a vector is unique.#23959
- The adjoint of a matrix-scalar product is the product of the adjoint and the conjugate.#23508
- The adjoint of a product of matrices is the product of the adjoints in reverse order.#23513
- The adjoint of a sum is the sum of the adjoints.#23507
- The Cauchy-Schwartz inequality#23913
- The Cauchy-Schwarz inequality#24092
- The Cayley-Hamilton theorem for a linear transformation#24046
- The Cayley-Hamilton theorem for a matrix.#23707
- The change of coordinates matrix between two bases exists and is unique#23996
- The characteristic polynomial applied to the matrix gives the 0 matrix.#23706
- The column space of a matrix is a vector space#24109
- The column space of an m-by-n matrix is a subspace of R^m (or C^m)#23876
- The composition of injective linear transformations is injective#24025
- The composition of invertible linear transformations is invertible#24027
- The composition of linear transformations is a linear transformation#24024
- The composition of surjective linear transformations is surjective#24026
- The condition number of matrix measures how close it is to being singular#23750
- The conjugate of a matrix-scalar product is the product of the conjugates.#23468
- The conjugate of a product of matrices is the product of the conjugates.#23469
- The conjugate of a sum of vectors in C^n is the sum of the conjugates#23791
- The conjugate of the sum of matrices is the sum of the conjugates.#23467
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