线性代数》英文专业词汇
has a unique value
invertible matrix
adjoint matrix
inverse matrix
elementary matrix
___
column n
rank of a matrix
linearly independent
linearly dependent
span
basis
___
___
___
___
identity matrix是什么意思
___
diagonalizable matrix
___ ___
singular value n
matrix norm
___
positive definite matrix
positive semi-definite matrix
negative definite matrix
negative semi-definite matrix
___ deals with the study of linear ___。One of the key concepts in linear algebra is the determinant。___ from a square matrix。The ___.
A matrix is a rectangular array of numbers that is used to ___。The identity matrix is a special type of matrix that has ones on the ___ matrix is equal to its transpose。while a skew-symmetric matrix is equal to the negative of ___ that the order of matrix ___.
The rank of a matrix is the maximum number of linearly independent rows or columns it contains。A matrix is invertible if and only if its determinant is nonzero。The adjoint matri
x is the transpose of the matrix of cofactors。while the inverse matrix is the product of the adjoint matrix and the reciprocal of the determinant.
___ are used to perform row or column ___ span a subspace。while linearly dependent vectors do not。The basis of a subspace is a set of linearly independent vectors that span the subspace。The n of a subspace is the number of ___.
___ matrix is a square matrix whose ___ Av = λv。where A is the matrix。v is the eigenvector。and λ is the ___ that is used to find the ___.
A diagonalizable matrix is a matrix that can be ___ canonical form is a way of representing a matrix as a block diagonal matrix。The singular value ___ of a matrix into three matrices.
The matrix norm is a n that assigns a non-negative value to a matrix。The ___ definite matrix is a matrix that has all positive eigenvalues。while a positive semi-definite matrix is a matrix that has all non-negative ___ definite matrix is a matrix that has all negative eigenvalues。while a negative semi-definite matrix is a matrix that has all non-___.

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