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In mathematics, the Khatri–Rao product or block Kronecker product of two partitioned matrices \mathbf and \mathbf is defined as : \mathbf \ast \mathbf = \left(\mathbf_ \otimes \mathbf_\right)_ in which the ''ij''-th block is the sized
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 vector ...
of the corresponding blocks of A and B, assuming the number of row and column partitions of both
matrices Matrix (: matrices or matrixes) or MATRIX may refer to: Science and mathematics * Matrix (mathematics), a rectangular array of numbers, symbols or expressions * Matrix (logic), part of a formula in prenex normal form * Matrix (biology), the ...
is equal. The size of the product is then . For example, if A and B both are partitioned matrices e.g.: : \mathbf = \left \begin \mathbf_ & \mathbf_ \\ \hline \mathbf_ & \mathbf_ \end \right= \left \begin 1 & 2 & 3 \\ 4 & 5 & 6 \\ \hline 7 & 8 & 9 \end \right,\quad \mathbf = \left \begin \mathbf_ & \mathbf_ \\ \hline \mathbf_ & \mathbf_ \end \right= \left \begin 1 & 4 & 7 \\ \hline 2 & 5 & 8 \\ 3 & 6 & 9 \end \right, we obtain: : \mathbf \ast \mathbf = \left \begin \mathbf_ \otimes \mathbf_ & \mathbf_ \otimes \mathbf_ \\ \hline \mathbf_ \otimes \mathbf_ & \mathbf_ \otimes \mathbf_ \end \right= \left \begin 1 & 2 & 12 & 21 \\ 4 & 5 & 24 & 42 \\ \hline 14 & 16 & 45 & 72 \\ 21 & 24 & 54 & 81 \end \right This is a submatrix of the Tracy–Singh product of the two matrices (each partition in this example is a partition in a corner of the Tracy–Singh product).


Column-wise Kronecker product

The column-wise
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 vector ...
of two matrices is a special case of the Khatri-Rao product as defined above, and may also be called ''the'' Khatri–Rao product. This product assumes the partitions of the matrices are their columns. In this case , , and for each ''j'': . The resulting product is a matrix of which each column is the Kronecker product of the corresponding columns of ''A'' and ''B''. Using the matrices from the previous examples with the columns partitioned: : \mathbf = \left \begin \mathbf_1 & \mathbf_2 & \mathbf_3 \end \right= \left \begin 1 & 2 & 3 \\ 4 & 5 & 6 \\ 7 & 8 & 9 \end \right,\quad \mathbf = \left \begin \mathbf_1 & \mathbf_2 & \mathbf_3 \end \right= \left \begin 1 & 4 & 7 \\ 2 & 5 & 8 \\ 3 & 6 & 9 \end \right, so that: : \mathbf \ast \mathbf = \left \begin \mathbf_1 \otimes \mathbf_1 & \mathbf_2 \otimes \mathbf_2 & \mathbf_3 \otimes \mathbf_3 \end \right= \left \begin 1 & 8 & 21 \\ 2 & 10 & 24 \\ 3 & 12 & 27 \\ 4 & 20 & 42 \\ 8 & 25 & 48 \\ 12 & 30 & 54 \\ 7 & 32 & 63 \\ 14 & 40 & 72 \\ 21 & 48 & 81 \end \right This column-wise version of the Khatri–Rao product is useful in linear algebra approaches to data analytical processing and in optimizing the solution of inverse problems dealing with a diagonal matrix. In 1996 the column-wise Khatri–Rao product was proposed to estimate the angles of arrival (AOAs) and delays of multipath signals and four coordinates of signals sources at a
digital antenna array Digital antenna array (DAA) is a smart antenna with multi channels digital beamforming, usually by using fast Fourier transform (FFT). The development and practical realization of digital antenna arrays theory started in 1962 under the guidanc ...
.


Face-splitting product

An alternative concept of the matrix product, which uses row-wise splitting of matrices with a given quantity of rows, was proposed by V. SlyusarAnna Esteve, Eva Boj & Josep Fortiana (2009): "Interaction Terms in Distance-Based Regression," ''Communications in Statistics – Theory and Methods'', 38:19, p. 350

/ref> in 1996. This matrix operation was named the "face-splitting product" of matrices or the "transposed Khatri–Rao product". This type of operation is based on row-by-row Kronecker product, Kronecker products of two matrices. Using the matrices from the previous examples with the rows partitioned: : \mathbf = \begin \mathbf_1 \\\hline \mathbf_2 \\\hline \mathbf_3\\ \end = \begin 1 & 2 & 3 \\\hline 4 & 5 & 6 \\\hline 7 & 8 & 9 \end ,\quad \mathbf = \begin \mathbf_1\\\hline \mathbf_2\\\hline \mathbf_3\\ \end = \begin 1 & 4 & 7 \\\hline 2 & 5 & 8 \\\hline 3 & 6 & 9 \end , the result can be obtained: : \mathbf \bull \mathbf = \begin \mathbf_1 \otimes \mathbf_1\\\hline \mathbf_2 \otimes \mathbf_2\\\hline \mathbf_3 \otimes \mathbf_3\\ \end = \begin 1 & 4 & 7 & 2 & 8 & 14 & 3 & 12 & 21 \\\hline 8 & 20 & 32 & 10 & 25 & 40 & 12 & 30 & 48 \\\hline 21 & 42 & 63 & 24 & 48 & 72 & 27 & 54 & 81 \end.


Main properties

In the following properties, the operator \bull denotes the row-wise Kronecker product (face-splitting product) and the operator \ast denotes the column-wise Kronecker product


Examples

Source: : \begin &\left( \begin 1 & 0 \\ 0 & 1 \\ 1 & 0 \end \bullet \begin 1 & 0 \\ 1 & 0 \\ 0 & 1 \end \right) \left( \begin 1 & 1 \\ 1 & -1 \end \otimes \begin 1 & 1 \\ 1 & -1 \end \right) \left( \begin \sigma_1 & 0 \\ 0 & \sigma_2 \\ \end \otimes \begin \rho_1 & 0 \\ 0 & \rho_2 \\ \end \right) \left( \begin x_1 \\ x_2 \end \ast \begin y_1 \\ y_2 \end \right) \\ pt = &\left( \begin 1 & 0 \\ 0 & 1 \\ 1 & 0 \end \bullet \begin 1 & 0 \\ 1 & 0 \\ 0 & 1 \end \right) \left( \begin 1 & 1 \\ 1 & -1 \end \begin \sigma_1 & 0 \\ 0 & \sigma_2 \\ \end \begin x_1 \\ x_2 \end \,\otimes\, \begin 1 & 1 \\ 1 & -1 \end \begin \rho_1 & 0 \\ 0 & \rho_2 \\ \end \begin y_1 \\ y_2 \end \right) \\ pt = & \begin 1 & 0 \\ 0 & 1 \\ 1 & 0 \end \begin 1 & 1 \\ 1 & -1 \end \begin \sigma_1 & 0 \\ 0 & \sigma_2 \\ \end \begin x_1 \\ x_2 \end \,\circ\, \begin 1 & 0 \\ 1 & 0 \\ 0 & 1 \end \begin 1 & 1 \\ 1 & -1 \end \begin \rho_1 & 0 \\ 0 & \rho_2 \\ \end \begin y_1 \\ y_2 \end . \end


Theorem

Source: If M = T^ \bullet \dots \bullet T^, where T^, \dots, T^ are independent components a random matrix T with independent identically distributed rows T_1, \dots, T_m\in \mathbb R^d, such that : E\left T_1x)^2\right= \left\, x\right\, _2^2 and E\left T_1 x)^p\right\frac \le \sqrt\, x\, _2, then for any vector x : \left, \left\, Mx\right\, _2 - \left\, x\right\, _2 \ < \varepsilon \left\, x\right\, _2 with probability 1 - \delta if the quantity of rows :m = (4a)^ \varepsilon^ \log 1/\delta + (2ae)\varepsilon^(\log 1/\delta)^c. In particular, if the entries of T are \pm 1 can get : m = O\left(\varepsilon^\log1/\delta + \varepsilon^\left(\frac\log1/\delta\right)^c\right) which matches the
Johnson–Lindenstrauss lemma In mathematics, the Johnson–Lindenstrauss lemma is a result named after William B. Johnson and Joram Lindenstrauss concerning low-distortion embeddings of points from high-dimensional into low-dimensional Euclidean space. The lemma states that ...
of m = O\left(\varepsilon^\log1/\delta\right) when \varepsilon is small.


Block face-splitting product

According to the definition of V. Slyusar the block face-splitting product of two partitioned matrices with a given quantity of rows in blocks : \mathbf = \left \begin \mathbf_ & \mathbf_ \\ \hline \mathbf_ & \mathbf_ \end \right ,\quad \mathbf = \left \begin \mathbf_ & \mathbf_ \\ \hline \mathbf_ & \mathbf_ \end \right, can be written as : : \mathbf
bull A bull is an intact (i.e., not Castration, castrated) adult male of the species ''Bos taurus'' (cattle). More muscular and aggressive than the females of the same species (i.e. cows proper), bulls have long been an important symbol cattle in r ...
\mathbf = \left \begin \mathbf_ \bull \mathbf_ & \mathbf_ \bull \mathbf_ \\ \hline \mathbf_ \bull \mathbf_ & \mathbf_ \bull \mathbf_ \end \right. The transposed block face-splitting product (or Block column-wise version of the Khatri–Rao product) of two partitioned matrices with a given quantity of columns in blocks has a view: : \mathbf
ast AST, Ast, or ast may refer to: Science and technology * Attention schema theory, of consciousness or subjective awareness Computing * Abstract syntax tree, a finite, labeled, directed tree used in computer science * Anamorphic stretch transform, ...
\mathbf = \left \begin \mathbf_ \ast \mathbf_ & \mathbf_ \ast \mathbf_ \\ \hline \mathbf_ \ast \mathbf_ & \mathbf_ \ast \mathbf_ \end \right


Main properties

#
Transpose In linear algebra, the transpose of a Matrix (mathematics), matrix is an operator which flips a matrix over its diagonal; that is, it switches the row and column indices of the matrix by producing another matrix, often denoted by (among other ...
: #:\left(\mathbf
ast AST, Ast, or ast may refer to: Science and technology * Attention schema theory, of consciousness or subjective awareness Computing * Abstract syntax tree, a finite, labeled, directed tree used in computer science * Anamorphic stretch transform, ...
\mathbf \right)^\textsf = \textbf^\textsf
bull A bull is an intact (i.e., not Castration, castrated) adult male of the species ''Bos taurus'' (cattle). More muscular and aggressive than the females of the same species (i.e. cows proper), bulls have long been an important symbol cattle in r ...
\mathbf^\textsfVadym Slyusar
New Matrix Operations for DSP
(Lecture). April 1999. – DOI: 10.13140/RG.2.2.31620.76164/1


Applications

The Face-splitting product and the Block Face-splitting product used in the
tensor In mathematics, a tensor is an algebraic object that describes a multilinear relationship between sets of algebraic objects associated with a vector space. Tensors may map between different objects such as vectors, scalars, and even other ...
-matrix theory of
digital antenna array Digital antenna array (DAA) is a smart antenna with multi channels digital beamforming, usually by using fast Fourier transform (FFT). The development and practical realization of digital antenna arrays theory started in 1962 under the guidanc ...
s. These operations are also used in: *
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and
Machine learning Machine learning (ML) is a field of study in artificial intelligence concerned with the development and study of Computational statistics, statistical algorithms that can learn from data and generalise to unseen data, and thus perform Task ( ...
systems to minimization of
convolution In mathematics (in particular, functional analysis), convolution is a operation (mathematics), mathematical operation on two function (mathematics), functions f and g that produces a third function f*g, as the integral of the product of the two ...
and
tensor sketch In statistics, machine learning and algorithms, a tensor sketch is a type of dimensionality reduction that is particularly efficient when applied to Vector (mathematics and physics), vectors that have tensor structure. Such a sketch can be used ...
operations, * A popular
Natural Language Processing Natural language processing (NLP) is a subfield of computer science and especially artificial intelligence. It is primarily concerned with providing computers with the ability to process data encoded in natural language and is thus closely related ...
models, and hypergraph models of similarity, *
Generalized linear array model In statistics, the generalized linear array model (GLAM) is used for analyzing data sets with array structures. It based on the generalized linear model with the design matrix written as a Kronecker product. Overview The generalized linear array ...
in
statistics Statistics (from German language, German: ', "description of a State (polity), state, a country") is the discipline that concerns the collection, organization, analysis, interpretation, and presentation of data. In applying statistics to a s ...
* Two- and multidimensional P-spline approximation of data, * Studies of genotype x environment interactions.Johannes W. R. Martini, Jose Crossa, Fernando H. Toledo, Jaime Cuevas. On Hadamard and Kronecker products in covariance structures for genotype x environment interaction.//Plant Genome. 2020;13:e20033. Page 5

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See also

*
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 vector ...
* Hadamard product (matrices), Hadamard product


Notes


References

* * * * {{DEFAULTSORT:Khatri-Rao Product Matrix theory