Seonglae ChoMatrix Multiplication 과 다르다
Tensor Products
Tensor product
In mathematics, the tensor product
V
⊗
W
{\displaystyle V\otimes W}
of two vector spaces V and W (over the same field) is a vector space to which is associated a bilinear map
V
×
W
→
V
⊗
W
{\displaystyle V\times W\rightarrow V\otimes W}
that maps a pair
(
v
,
w
)
,
 
v
∈
V
,
w
∈
W
{\displaystyle (v,w),\ v\in V,w\in W}
to an element of
V
⊗
W
{\displaystyle V\otimes W}
denoted
v
⊗
w
{\displaystyle v\otimes w}
.
https://en.wikipedia.org/wiki/Tensor_product
Kronecker product
In mathematics, the Kronecker product, sometimes denoted by ⊗, is an operation on two matrices of arbitrary size resulting in a block matrix. It is a specialization of the tensor product (which is denoted by the same symbol) from vectors to matrices and gives the matrix of the tensor product linear map with respect to a standard choice of basis. The Kronecker product is to be distinguished from the usual matrix multiplication, which is an entirely different operation. The Kronecker product is also sometimes called matrix direct product.[1]
https://en.wikipedia.org/wiki/Kronecker_product
Hadamard product (matrices)
In mathematics, the Hadamard product is a binary operation that takes in two matrices of the same dimensions and returns a matrix of the multiplied corresponding elements. This operation can be thought as a "naive matrix multiplication" and is different from the matrix product. It is attributed to, and named after, either French mathematician Jacques Hadamard or German mathematician Issai Schur.
https://en.wikipedia.org/wiki/Hadamard_product_(matrices)
