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Qingwen Hu – författare

Visar alla böcker från författaren Qingwen Hu. Handla med fri frakt och snabb leverans.

4 produkter

  1. Qingwen Hu - Concise Introduction to Linear Algebra, Häftad. Tillgänglighet: Lägg i varukorg

    Concise Introduction to Linear Algebra

    Av Qingwen Hu

    Häftad, 2020

    807 kr

    Lägg i varukorg

    Concise Introduction to Linear Algebra deals with the subject of linear algebra, covering vectors and linear systems, vector spaces, orthogonality, determinants, eigenvalues and eigenvectors, singular value decomposition. It adopts an efficient approach to lead students from vectors, matrices …

  2. Qingwen Hu - Concise Introduction to Linear Algebra, Inbunden. Tillgänglighet: Lägg i varukorg

    Concise Introduction to Linear Algebra

    Av Qingwen Hu

    Inbunden, 2017

    1520 kr

    Lägg i varukorg

    Concise Introduction to Linear Algebra deals with the subject of linear algebra, covering vectors and linear systems, vector spaces, orthogonality, determinants, eigenvalues and eigenvectors, singular value decomposition. It adopts an efficient approach to lead students from vectors, matrices …

  3. Qingwen Hu - Concise Introduction to Linear Algebra, E-bok. Tillgänglighet: Lägg i varukorg

    Concise Introduction to Linear Algebra

    Av Qingwen Hu

    E-bok, 2017

    953 kr

    Lägg i varukorg

    Concise Introduction to Linear Algebra deals with the subject of linear algebra, covering vectors and linear systems, vector spaces, orthogonality, determinants, eigenvalues and eigenvectors, singular value decomposition. It adopts an efficient approach to lead students from vectors, matrices …

  4. Qingwen Hu - Concise Introduction to Linear Algebra, E-bok. Tillgänglighet: Lägg i varukorg

    Concise Introduction to Linear Algebra

    Av Qingwen Hu

    E-bok, 2017

    932 kr

    Lägg i varukorg

    Concise Introduction to Linear Algebra deals with the subject of linear algebra, covering vectors and linear systems, vector spaces, orthogonality, determinants, eigenvalues and eigenvectors, singular value decomposition. It adopts an efficient approach to lead students from vectors, matrices …