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  2. Gaussian beam - Wikipedia

    en.wikipedia.org/wiki/Gaussian_beam

    The Gaussian function has a 1/e 2 diameter (2w as used in the text) about 1.7 times the FWHM.. At a position z along the beam (measured from the focus), the spot size parameter w is given by a hyperbolic relation: [1] = + (), where [1] = is called the Rayleigh range as further discussed below, and is the refractive index of the medium.

  3. Gaussian function - Wikipedia

    en.wikipedia.org/wiki/Gaussian_function

    In mathematics, a Gaussian function, often simply referred to as a Gaussian, is a function of the base form = ⁡ () ...

  4. Gaussian probability space - Wikipedia

    en.wikipedia.org/wiki/Gaussian_probability_space

    In probability theory particularly in the Malliavin calculus, a Gaussian probability space is a probability space together with a Hilbert space of mean zero, real-valued Gaussian random variables. Important examples include the classical or abstract Wiener space with some suitable collection of Gaussian random variables.

  5. Gaussian measure - Wikipedia

    en.wikipedia.org/wiki/Gaussian_measure

    Gaussian measures with mean = are known as centered Gaussian measures. The Dirac measure δ μ {\displaystyle \delta _{\mu }} is the weak limit of γ μ , σ 2 n {\displaystyle \gamma _{\mu ,\sigma ^{2}}^{n}} as σ → 0 {\displaystyle \sigma \to 0} , and is considered to be a degenerate Gaussian measure ; in contrast, Gaussian measures with ...

  6. Normal distribution - Wikipedia

    en.wikipedia.org/wiki/Normal_distribution

    All these extensions are also called normal or Gaussian laws, so a certain ambiguity in names exists. The multivariate normal distribution describes the Gaussian law in the k-dimensional Euclidean space. A vector X ∈ R k is multivariate-normally distributed if any linear combination of its components Σ k j=1 a j X j has a (univariate) normal ...

  7. EM algorithm and GMM model - Wikipedia

    en.wikipedia.org/wiki/EM_Algorithm_And_GMM_Model

    The EM algorithm consists of two steps: the E-step and the M-step. Firstly, the model parameters and the () can be randomly initialized. In the E-step, the algorithm tries to guess the value of () based on the parameters, while in the M-step, the algorithm updates the value of the model parameters based on the guess of () of the E-step.

  8. Samuel Francis Boys - Wikipedia

    en.wikipedia.org/wiki/Samuel_Francis_Boys

    Boys is best known for the introduction of Gaussian orbitals into ab initio quantum chemistry. [ 8 ] [ 9 ] Almost all basis sets used in computational chemistry now employ these orbitals. [ 10 ] Frank Boys was also one of the first scientists to use digital computers for calculations on polyatomic molecules.

  9. Gaussian process - Wikipedia

    en.wikipedia.org/wiki/Gaussian_process

    Inference of continuous values with a Gaussian process prior is known as Gaussian process regression, or kriging; extending Gaussian process regression to multiple target variables is known as cokriging. [26] Gaussian processes are thus useful as a powerful non-linear multivariate interpolation tool. Kriging is also used to extend Gaussian ...