AIMS Lecture Notes 2006 3. Review of Matrix Algebra Peter J. Olver
... The identity matrix is a particular example of a diagonal matrix . In general, a square matrix A is diagonal if all its off-diagonal entries are zero: a ij = 0 for all i 6= j. We will sometimes write D = diag (c1 , . . . , cn ) for the n × n diagonalmatrix with diagonal entries ...
... The identity matrix is a particular example of a diagonal matrix . In general, a square matrix A is diagonal if all its off-diagonal entries are zero: a ij = 0 for all i 6= j. We will sometimes write D = diag (c1 , . . . , cn ) for the n × n diagonalmatrix with diagonal entries ...
A note on the convexity of the realizable set of eigenvalues for
... Many necessary conditions for an n–tuple of numbers to be realizable are known, and there are also several known sufficient conditions. Nevertheless, for n > 4, the realizable n–tuples have not yet been fully characterized. Sources of information on the inverse eigenvalue problem for symmetric nonnega ...
... Many necessary conditions for an n–tuple of numbers to be realizable are known, and there are also several known sufficient conditions. Nevertheless, for n > 4, the realizable n–tuples have not yet been fully characterized. Sources of information on the inverse eigenvalue problem for symmetric nonnega ...
Normal subgroups and factor groups(TA Peng)
... if we could say that H is a normal subset of G. This may well be too much to hope for. But actually to produce a group G with a non-empty subset H and an element x0 such that Hx = HxH for all x but Hx0 f x 0 H seems a difficult problem." (Note that Hx o Hy = HxHy means Hxy = HxHy which gives HxH = H ...
... if we could say that H is a normal subset of G. This may well be too much to hope for. But actually to produce a group G with a non-empty subset H and an element x0 such that Hx = HxH for all x but Hx0 f x 0 H seems a difficult problem." (Note that Hx o Hy = HxHy means Hxy = HxHy which gives HxH = H ...
Matrix multiplication: a group-theoretic approach 1 Notation 2
... If there are no z’s then by equating componentwise we get that ∀i ≤ 3, ai +a0i = bi +b0i = 0 and hence si = ti , ∀i ≤ 3. If there are 2 z’s then assuming without loss of generality that J3 = 0 we get that (a1 , b1 )z(a01 , b01 )(a2 , b2 )z(a02 , b02 )(a3 , b3 )(a03 , b03 ) = (a1 , b1 )(b01 , a01 )(b ...
... If there are no z’s then by equating componentwise we get that ∀i ≤ 3, ai +a0i = bi +b0i = 0 and hence si = ti , ∀i ≤ 3. If there are 2 z’s then assuming without loss of generality that J3 = 0 we get that (a1 , b1 )z(a01 , b01 )(a2 , b2 )z(a02 , b02 )(a3 , b3 )(a03 , b03 ) = (a1 , b1 )(b01 , a01 )(b ...
Jordan normal form
In linear algebra, a Jordan normal form (often called Jordan canonical form)of a linear operator on a finite-dimensional vector space is an upper triangular matrix of a particular form called a Jordan matrix, representing the operator with respect to some basis. Such matrix has each non-zero off-diagonal entry equal to 1, immediately above the main diagonal (on the superdiagonal), and with identical diagonal entries to the left and below them. If the vector space is over a field K, then a basis with respect to which the matrix has the required form exists if and only if all eigenvalues of the matrix lie in K, or equivalently if the characteristic polynomial of the operator splits into linear factors over K. This condition is always satisfied if K is the field of complex numbers. The diagonal entries of the normal form are the eigenvalues of the operator, with the number of times each one occurs being given by its algebraic multiplicity.If the operator is originally given by a square matrix M, then its Jordan normal form is also called the Jordan normal form of M. Any square matrix has a Jordan normal form if the field of coefficients is extended to one containing all the eigenvalues of the matrix. In spite of its name, the normal form for a given M is not entirely unique, as it is a block diagonal matrix formed of Jordan blocks, the order of which is not fixed; it is conventional to group blocks for the same eigenvalue together, but no ordering is imposed among the eigenvalues, nor among the blocks for a given eigenvalue, although the latter could for instance be ordered by weakly decreasing size.The Jordan–Chevalley decomposition is particularly simple with respect to a basis for which the operator takes its Jordan normal form. The diagonal form for diagonalizable matrices, for instance normal matrices, is a special case of the Jordan normal form.The Jordan normal form is named after Camille Jordan.