This function does exactly what Matlab KRON does, but for large full matrices, the engine uses BSXFUN to accelerate the calculation.
Another advantage is no intermediate large matrices are generated (four temporary arrays in case of KRON).
Here is the benchmark code and result:
clear,
gain=[];
mem = memory;
maxn = (mem.MaxPossibleArrayBytes/32)^0.25;
n = 10:10:maxn;
for sz=n
A=rand(sz); B=rand(sz);
t1=Inf;
for ntry=1:10
tic; K = kron(A,B); t1=min(t1,toc);
end
clear K
t2=Inf;
for ntry=1:10
tic; K = kronecker(A,B); t2=min(t2,toc);
end
clear K
gain(end+1) = t1/t2;
end
fprintf('Size A/B Speed gain\n');
fprintf(' %02d %1.2f \n', [n; gain]);
Size A/B Speed gain
10 1.17
20 3.48
30 3.78
40 3.73
50 3.68
60 4.22
70 3.81
引用格式
Bruno Luong (2024). kronecker (https://www.mathworks.com/matlabcentral/fileexchange/24499-kronecker), MATLAB Central File Exchange. 检索来源 .
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致谢
启发作品: Kronecker product
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