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  2. Non-linear sigma model - Wikipedia

    en.wikipedia.org/wiki/Non-linear_sigma_model

    In quantum field theory, a nonlinear σ model describes a field Σ that takes on values in a nonlinear manifold called the target manifold T.The non-linear σ-model was introduced by Gell-Mann & Lévy (1960, §6), who named it after a field corresponding to a spinless meson called σ in their model. [1]

  3. Normal distribution - Wikipedia

    en.wikipedia.org/wiki/Normal_distribution

    The standard deviation of the distribution is (sigma). A random variable with a Gaussian distribution is said to be normally distributed , and is called a normal deviate . Normal distributions are important in statistics and are often used in the natural and social sciences to represent real-valued random variables whose distributions are not ...

  4. σ-algebra - Wikipedia

    en.wikipedia.org/wiki/Σ-algebra

    In mathematical analysis and in probability theory, a σ-algebra ("sigma algebra"; also σ-field, where the σ comes from the German "Summe" [1]) on a set X is a nonempty collection Σ of subsets of X closed under complement, countable unions, and countable intersections. The ordered pair (,) is called a measurable space.

  5. Sigma - Wikipedia

    en.wikipedia.org/wiki/Sigma

    Sigma algebra also includes terms such as: σ(A), denoting the generated sigma-algebra of a set A; Σ-finite measure (see measure theory) In number theory, σ is included in various divisor functions, especially the sigma function or sum-of-divisors function. In applied mathematics, σ(T) denotes the spectrum of a linear map T.

  6. Sigma model - Wikipedia

    en.wikipedia.org/wiki/Sigma_model

    The model may or may not be quantized. An example of the non-quantized version is the Skyrme model; it cannot be quantized due to non-linearities of power greater than 4. In general, sigma models admit (classical) topological soliton solutions, for example, the skyrmion for the Skyrme model.

  7. Singular value decomposition - Wikipedia

    en.wikipedia.org/wiki/Singular_value_decomposition

    In linear algebra, the singular value decomposition (SVD) is a factorization of a real or complex matrix into a rotation, followed by a rescaling followed by another rotation. It generalizes the eigendecomposition of a square normal matrix with an orthonormal eigenbasis to any ⁠ m × n {\displaystyle m\times n} ⁠ matrix.

  8. Weierstrass functions - Wikipedia

    en.wikipedia.org/wiki/Weierstrass_functions

    The relation between the sigma, zeta, and ℘ functions is analogous to that between the sine, cotangent, and squared cosecant functions: the logarithmic derivative of the sine is the cotangent, whose derivative is negative the squared cosecant.

  9. Sigmoid function - Wikipedia

    en.wikipedia.org/wiki/Sigmoid_function

    Examples of the application of the logistic S-curve to the response of crop yield (wheat) to both the soil salinity and depth to water table in the soil are shown in modeling crop response in agriculture. In artificial neural networks, sometimes non-smooth functions are used instead for efficiency; these are known as hard sigmoids.