Kronecker tensorial product. Weighted array replication
P = kron(A, B) P = A .*. B
Arrays of size (a1, a2, ..) and (b1, b2, ..), with any number of dimensions.
If A
or B
is sparse, the other one
can't be an hypermatrix.
Supported encodings and types: integer, real, complex, polynomial, rational, sparse.
Array of A
and B
data type,
and of size (a1*b1, a2*b2, ..).
If A
or B
is sparse,
P
is sparse.
kron(A,B)
or A .*. B
returns the
Kronecker tensor product of two matrices or hypermatricesA
and
B
. The resulting matrix has the following block
form:
If A
is a m x n
matrix and
B
a p x q x r
hypermatrix then
A.*.B
is a (m*p) x (n*q) x (1*r)
hypermatrix.
A = [1 3 ; 2 4] B = [1 10 100] kron(A, B) A .*. B B .*. A | ![]() | ![]() |
--> A = [1 3 ; 2 4] A = 1. 3. 2. 4. --> B = [1 10 100] B = 1. 10. 100. --> kron(A, B) ans = 1. 10. 100. 3. 30. 300. 2. 20. 200. 4. 40. 400. --> A .*. B ans = 1. 10. 100. 3. 30. 300. 2. 20. 200. 4. 40. 400. --> B .*. A ans = 1. 3. 10. 30. 100. 300. 2. 4. 20. 40. 200. 400.
With sparse matrices:
--> P = [-1 0 1 10] .*. sparse([0 1 2]) P = ( 1, 12) sparse matrix ( 1, 2) -1. ( 1, 3) -2. ( 1, 8) 1. ( 1, 9) 2. ( 1, 11) 10. ( 1, 12) 20. --> full(P) ans = 0. -1. -2. 0. 0. 0. 0. 1. 2. 0. 10. 20.
With complex numbers:
--> A = [-1 1 ; -%i %i] A = -1. 1. -i i --> A .*. A ans = 1. -1. -1. 1. i -i -i i i -i -i i -1. 1. 1. -1.
With hypermatrices:
Version | Description |
5.5.1 | Extension to hypermatrices |