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  2. Dot product - Wikipedia

    en.wikipedia.org/wiki/Dot_product

    In such a presentation, the notions of length and angle are defined by means of the dot product. The length of a vector is defined as the square root of the dot product of the vector by itself, and the cosine of the (non oriented) angle between two vectors of length one is defined as their dot product. So the equivalence of the two definitions ...

  3. Inner product space - Wikipedia

    en.wikipedia.org/wiki/Inner_product_space

    More abstractly, the outer product is the bilinear map ⁡ (,) sending a vector and a covector to a rank 1 linear transformation (simple tensor of type (1, 1)), while the inner product is the bilinear evaluation map given by evaluating a covector on a vector; the order of the domain vector spaces here reflects the covector/vector distinction.

  4. Scalar multiplication - Wikipedia

    en.wikipedia.org/wiki/Scalar_multiplication

    Scalar multiplication of a vector by a factor of 3 stretches the vector out. The scalar multiplications −a and 2a of a vector a. In mathematics, scalar multiplication is one of the basic operations defining a vector space in linear algebra [1] [2] [3] (or more generally, a module in abstract algebra [4] [5]).

  5. Cosine similarity - Wikipedia

    en.wikipedia.org/wiki/Cosine_similarity

    The most noteworthy property of cosine similarity is that it reflects a relative, rather than absolute, comparison of the individual vector dimensions. For any positive constant and vector , the vectors and are maximally similar. The measure is thus most appropriate for data where frequency is more important than absolute values; notably, term ...

  6. Riemannian manifold - Wikipedia

    en.wikipedia.org/wiki/Riemannian_manifold

    The set () of smooth vector fields along is a vector space under pointwise vector addition and scalar multiplication. [18] One can also pointwise multiply a smooth vector field along γ {\displaystyle \gamma } by a smooth function f : [ 0 , 1 ] → R {\displaystyle f:[0,1]\to \mathbb {R} } :

  7. Geometric Brownian motion - Wikipedia

    en.wikipedia.org/wiki/Geometric_Brownian_motion

    Geometric Brownian motion is used to model stock prices in the Black–Scholes model and is the most widely used model of stock price behavior. [4] Some of the arguments for using GBM to model stock prices are: The expected returns of GBM are independent of the value of the process (stock price), which agrees with what we would expect in ...

  8. Cutting stock problem - Wikipedia

    en.wikipedia.org/wiki/Cutting_stock_problem

    Industrial applications of cutting-stock problems for high production volumes arise especially when basic material is produced in large rolls that are further cut into smaller units (see roll slitting). This is done e.g. in paper and plastic film industries but also in production of flat metals like steel or brass.

  9. Hadamard product (matrices) - Wikipedia

    en.wikipedia.org/wiki/Hadamard_product_(matrices)

    The Hadamard product operates on identically shaped matrices and produces a third matrix of the same dimensions. In mathematics, the Hadamard product (also known as the element-wise product, entrywise product [1]: ch. 5 or Schur product [2]) is a binary operation that takes in two matrices of the same dimensions and returns a matrix of the multiplied corresponding elements.