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In linear algebra, a column vector or column matrix is an ''m'' × 1 matrix, that is, a matrix consisting of a single column of ''m'' elements, : Similarly, a row vector or row matrix is a 1 × ''m'' matrix, that is, a matrix consisting of a single row of ''m'' elements〔, p. 8〕 : Throughout, boldface is used for the row and column vectors. The transpose (indicated by T) of a row vector is a column vector : and the transpose of a column vector is a row vector : The set of all row vectors forms a vector space called row space, similarly the set of all column vectors forms a vector space called column space. The dimensions of the row and column spaces equals the number of entries in the row or column vector. The column space can be viewed as the dual space to the row space, since any linear functional on the space of column vectors can be represented uniquely as an inner product with a specific row vector. == Notation == To simplify writing column vectors in-line with other text, sometimes they are written as row vectors with the transpose operation applied to them. : or : Some authors also use the convention of writing both column vectors and row vectors as rows, but separating row vector elements with commas and column vector elements with semicolons (see alternative notation 2 in the table below). | align=center| |- | Alternative notation 1 (commas, transpose signs) | align=center| | align=center| |- | Alternative notation 2 (commas and semicolons, no transpose signs) | align=center| | align=center| |} 抄文引用元・出典: フリー百科事典『 ウィキペディア(Wikipedia)』 ■ウィキペディアで「Row and column vectors」の詳細全文を読む スポンサード リンク
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