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  2. Inner product space - Wikipedia

    en.wikipedia.org/wiki/Inner_product_space

    In mathematics, an inner product space (or, rarely, a Hausdorff pre-Hilbert space [1] [2]) is a real vector space or a complex vector space with an operation called an inner product. The inner product of two vectors in the space is a scalar , often denoted with angle brackets such as in a , b {\displaystyle \langle a,b\rangle } .

  3. Frobenius inner product - Wikipedia

    en.wikipedia.org/wiki/Frobenius_inner_product

    In mathematics, the Frobenius inner product is a binary operation that takes two matrices and returns a scalar.It is often denoted , .The operation is a component-wise inner product of two matrices as though they are vectors, and satisfies the axioms for an inner product.

  4. Indefinite inner product space - Wikipedia

    en.wikipedia.org/wiki/Indefinite_inner_product_space

    On a Krein space, the Hilbert inner product is positive definite, giving the structure of a Hilbert space (under a suitable topology). Under the weaker constraint K ± ⊂ K ± 0 {\displaystyle K_{\pm }\subset K_{\pm 0}} , some elements of the neutral subspace K 0 {\displaystyle K_{0}} may still be neutral in the Hilbert inner product, but many ...

  5. Dot product - Wikipedia

    en.wikipedia.org/wiki/Dot_product

    It is often called the inner product (or rarely the projection product) of Euclidean space, even though it is not the only inner product that can be defined on Euclidean space (see Inner product space for more). Algebraically, the dot product is the sum of the products of the corresponding entries of the two sequences of numbers.

  6. Normed vector space - Wikipedia

    en.wikipedia.org/wiki/Normed_vector_space

    An inner product space is a normed vector space whose norm is the square root of the inner product of a vector and itself. The Euclidean norm of a Euclidean vector space is a special case that allows defining Euclidean distance by the formula d ( A , B ) = ‖ A B → ‖ . {\displaystyle d(A,B)=\|{\overrightarrow {AB}}\|.}

  7. Orthonormality - Wikipedia

    en.wikipedia.org/wiki/Orthonormality

    The Gram-Schmidt theorem, together with the axiom of choice, guarantees that every vector space admits an orthonormal basis. This is possibly the most significant use of orthonormality, as this fact permits operators on inner-product spaces to be discussed in terms of their action on the space's orthonormal basis vectors. What results is a deep ...

  8. Cauchy–Schwarz inequality - Wikipedia

    en.wikipedia.org/wiki/Cauchy–Schwarz_inequality

    where , is the inner product.Examples of inner products include the real and complex dot product; see the examples in inner product.Every inner product gives rise to a Euclidean norm, called the canonical or induced norm, where the norm of a vector is denoted and defined by ‖ ‖:= , , where , is always a non-negative real number (even if the inner product is complex-valued).

  9. Petersson inner product - Wikipedia

    en.wikipedia.org/wiki/Petersson_inner_product

    The integral is absolutely convergent and the Petersson inner product is a positive definite Hermitian form. For the Hecke operators T n {\displaystyle T_{n}} , and for forms f , g {\displaystyle f,g} of level Γ 0 {\displaystyle \Gamma _{0}} , we have: