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  2. Kernel (linear algebra) - Wikipedia

    en.wikipedia.org/wiki/Kernel_(linear_algebra)

    The left null space of A is the same as the kernel of A T. The left null space of A is the orthogonal complement to the column space of A, and is dual to the cokernel of the associated linear transformation. The kernel, the row space, the column space, and the left null space of A are the four fundamental subspaces associated with the matrix A.

  3. Symbolab - Wikipedia

    en.wikipedia.org/wiki/Symbolab

    Symbolab is an answer engine [1] that provides step-by-step solutions to mathematical problems in a range of subjects. [2] It was originally developed by Israeli start-up company EqsQuest Ltd., under whom it was released for public use in 2011. In 2020, the company was acquired by American educational technology website Course Hero. [3] [4]

  4. Flux balance analysis - Wikipedia

    en.wikipedia.org/wiki/Flux_balance_analysis

    The analysis of the null space of matrices is implemented in software packages specialized for matrix operations such as Matlab and Octave. Determination of the null space of S {\displaystyle \scriptstyle \mathbf {S} } tells us all the possible collections of flux vectors (or linear combinations thereof) that balance fluxes within the ...

  5. Moore–Penrose inverse - Wikipedia

    en.wikipedia.org/wiki/Moore–Penrose_inverse

    SciPy adds a function scipy.linalg.pinv that uses a least-squares solver. The MASS package for R provides a calculation of the Moore–Penrose inverse through the ginv function. [ 24 ] The ginv function calculates a pseudoinverse using the singular value decomposition provided by the svd function in the base R package.

  6. Singular value decomposition - Wikipedia

    en.wikipedia.org/wiki/Singular_value_decomposition

    Mathematical applications of the SVD include computing the pseudoinverse, matrix approximation, and determining the rank, range, and null space of a matrix. The SVD is also extremely useful in all areas of science, engineering , and statistics , such as signal processing , least squares fitting of data, and process control .

  7. Null (mathematics) - Wikipedia

    en.wikipedia.org/wiki/Null_(mathematics)

    In a vector space, the null vector is the neutral element of vector addition; depending on the context, a null vector may also be a vector mapped to some null by a function under consideration (such as a quadratic form coming with the vector space, see null vector, a linear mapping given as matrix product or dot product, [4] a seminorm in a ...

  8. Course Hero buys Symbolab in a rare edtech acquisition

    www.aol.com/news/course-hero-buys-symbolab-rare...

    The 9-person Symbolab team, based in Tel Aviv, will join Course Hero . The platforms will live under independent branding for the near future, according to Andrew Grauer, CEO of Course Hero.

  9. Linear algebra - Wikipedia

    en.wikipedia.org/wiki/Linear_algebra

    For example, given a linear map T : V → W, the image T(V) of V, and the inverse image T −1 (0) of 0 (called kernel or null space), are linear subspaces of W and V, respectively. Another important way of forming a subspace is to consider linear combinations of a set S of vectors: the set of all sums