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  2. Eight-point algorithm - Wikipedia

    en.wikipedia.org/wiki/Eight-point_algorithm

    In theory, this algorithm can be used also for the fundamental matrix, but in practice the normalized eight-point algorithm, described by Richard Hartley in 1997, is better suited for this case. The algorithm's name derives from the fact that it estimates the essential matrix or the fundamental matrix from a set of eight (or more) corresponding ...

  3. Diffusion map - Wikipedia

    en.wikipedia.org/wiki/Diffusion_map

    Diffusion maps exploit the relationship between heat diffusion and random walk Markov chain.The basic observation is that if we take a random walk on the data, walking to a nearby data-point is more likely than walking to another that is far away.

  4. CITE-Seq - Wikipedia

    en.wikipedia.org/wiki/CITE-Seq

    Analysis of single-cell sequencing presents many challenges, such as determining the best way to normalize the data. [8] Due to a new level of complications that arise from sequencing of both proteins and transcripts at a single-cell level, the developers of CITE-Seq and their collaborators are maintaining several tools to help with data analysis.

  5. Essential matrix - Wikipedia

    en.wikipedia.org/wiki/Essential_matrix

    The essential matrix can be seen as a precursor to the fundamental matrix, .Both matrices can be used for establishing constraints between matching image points, but the fundamental matrix can only be used in relation to calibrated cameras since the inner camera parameters (matrices and ′) must be known in order to achieve the normalization.

  6. Normal matrix - Wikipedia

    en.wikipedia.org/wiki/Normal_matrix

    Let A be a square matrix. Then by Schur decomposition it is unitary similar to an upper-triangular matrix, say, B. If A is normal, so is B. But then B must be diagonal, for, as noted above, a normal upper-triangular matrix is diagonal. The spectral theorem permits the classification of normal matrices in terms of their spectra, for example:

  7. Matrix normal distribution - Wikipedia

    en.wikipedia.org/wiki/Matrix_normal_distribution

    The probability density function for the random matrix X (n × p) that follows the matrix normal distribution , (,,) has the form: (,,) = ⁡ ([() ()]) / | | / | | /where denotes trace and M is n × p, U is n × n and V is p × p, and the density is understood as the probability density function with respect to the standard Lebesgue measure in , i.e.: the measure corresponding to integration ...

  8. At least 2 dead after severe weather moved through ...

    www.aol.com/coast-coast-storms-could-bring...

    At least two people have died as severe storms and tornadoes tore through parts of Texas and Mississippi on Saturday, officials said, while a parade of atmospheric river-fueled storms batters the ...

  9. Smith normal form - Wikipedia

    en.wikipedia.org/wiki/Smith_normal_form

    In mathematics, the Smith normal form (sometimes abbreviated SNF [1]) is a normal form that can be defined for any matrix (not necessarily square) with entries in a principal ideal domain (PID). The Smith normal form of a matrix is diagonal, and can be obtained from the original matrix by multiplying on the left and right by invertible square ...