Everything being the same, then why does matrix C give different values in the two codes?

조회 수: 2 (최근 30일)
Sadiq Akbar
Sadiq Akbar 2021년 10월 16일
댓글: Sadiq Akbar 2021년 10월 19일
All the values are the same in both the codes, then why does matrix C give different values in both the codes?
code1:
u=[30 50 110];
M=10;
N=4;
K=3;
d=0.5;
fn=@(u,k) exp(1j*2*pi*d*(0:k-1).' * sind(u));
A=fn(u,M);
B=fn(u,N);
C=kron(B,A);
code2
u=[30 50 110];
M=10;
N=4;
K=3;
d=0.5;
C = STM(u,M,N,d);
function C = STM(u,M,N,d)
A=exp(1j*2*pi*d*(0:M-1).'*sind(u));
B=exp(1j*2*pi*d*(0:N-1).'*sind(u));
C = zeros(size(A, 1)*size(B, 1), length(u));
for idxK = 1 : 1 : length(u)
C(:, idxK) = kron(B(:, idxK), A(:, idxK));
end
end

이 질문에 답변하려면 로그인하십시오.

답변 (1개)

Cris LaPierre
Cris LaPierre 2021년 10월 16일
Because they are not the same?
Your output should be [size(A, 1)*size(B, 1), size(A, 2)*size(B, 2)]
See the More About > Kroeneker Tensor Product for what kron is calculating.
  댓글 수: 3
이전 댓글 1개 표시
Cris LaPierre
Cris LaPierre 2021년 10월 16일
Ran in:
Then you misunderstand what the Kroeneker Tensor Product is.
C is a 40x9 matrix in your first code.
u=[30 50 110];
M=10;
N=4;
K=3;
d=0.5;
fn=@(u,k) exp(1j*2*pi*d*(0:k-1).' * sind(u));
A=fn(u,M);
B=fn(u,N);
C=kron(B,A)
C =
1.0000 + 0.0000i 1.0000 + 0.0000i 1.0000 + 0.0000i 1.0000 + 0.0000i 1.0000 + 0.0000i 1.0000 + 0.0000i 1.0000 + 0.0000i 1.0000 + 0.0000i 1.0000 + 0.0000i 0.0000 + 1.0000i -0.7418 + 0.6706i -0.9821 + 0.1883i 0.0000 + 1.0000i -0.7418 + 0.6706i -0.9821 + 0.1883i 0.0000 + 1.0000i -0.7418 + 0.6706i -0.9821 + 0.1883i -1.0000 + 0.0000i 0.1006 - 0.9949i 0.9291 - 0.3699i -1.0000 + 0.0000i 0.1006 - 0.9949i 0.9291 - 0.3699i -1.0000 + 0.0000i 0.1006 - 0.9949i 0.9291 - 0.3699i -0.0000 - 1.0000i 0.5925 + 0.8056i -0.8428 + 0.5383i -0.0000 - 1.0000i 0.5925 + 0.8056i -0.8428 + 0.5383i -0.0000 - 1.0000i 0.5925 + 0.8056i -0.8428 + 0.5383i 1.0000 - 0.0000i -0.9797 - 0.2003i 0.7263 - 0.6874i 1.0000 - 0.0000i -0.9797 - 0.2003i 0.7263 - 0.6874i 1.0000 - 0.0000i -0.9797 - 0.2003i 0.7263 - 0.6874i 0.0000 + 1.0000i 0.8611 - 0.5084i -0.5839 + 0.8118i 0.0000 + 1.0000i 0.8611 - 0.5084i -0.5839 + 0.8118i 0.0000 + 1.0000i 0.8611 - 0.5084i -0.5839 + 0.8118i -1.0000 + 0.0000i -0.2978 + 0.9546i 0.4205 - 0.9073i -1.0000 + 0.0000i -0.2978 + 0.9546i 0.4205 - 0.9073i -1.0000 + 0.0000i -0.2978 + 0.9546i 0.4205 - 0.9073i -0.0000 - 1.0000i -0.4192 - 0.9079i -0.2421 + 0.9702i -0.0000 - 1.0000i -0.4192 - 0.9079i -0.2421 + 0.9702i -0.0000 - 1.0000i -0.4192 - 0.9079i -0.2421 + 0.9702i 1.0000 - 0.0000i 0.9198 + 0.3924i 0.0551 - 0.9985i 1.0000 - 0.0000i 0.9198 + 0.3924i 0.0551 - 0.9985i 1.0000 - 0.0000i 0.9198 + 0.3924i 0.0551 - 0.9985i 0.0000 + 1.0000i -0.9455 + 0.3257i 0.1340 + 0.9910i 0.0000 + 1.0000i -0.9455 + 0.3257i 0.1340 + 0.9910i 0.0000 + 1.0000i -0.9455 + 0.3257i 0.1340 + 0.9910i 0.0000 + 1.0000i 0.0000 + 1.0000i 0.0000 + 1.0000i -0.7418 + 0.6706i -0.7418 + 0.6706i -0.7418 + 0.6706i -0.9821 + 0.1883i -0.9821 + 0.1883i -0.9821 + 0.1883i -1.0000 + 0.0000i -0.6706 - 0.7418i -0.1883 - 0.9821i -0.6706 - 0.7418i 0.1006 - 0.9949i 0.6023 - 0.7983i -0.1883 - 0.9821i 0.6023 - 0.7983i 0.9291 - 0.3699i -0.0000 - 1.0000i 0.9949 + 0.1006i 0.3699 + 0.9291i 0.7418 - 0.6706i 0.5925 + 0.8056i -0.4412 + 0.8974i 0.9821 - 0.1883i 0.0885 + 0.9961i -0.8428 + 0.5383i 1.0000 - 0.0000i -0.8056 + 0.5925i -0.5383 - 0.8428i 0.6706 + 0.7418i -0.9797 - 0.2003i 0.2642 - 0.9645i 0.1883 + 0.9821i -0.7336 - 0.6796i 0.7263 - 0.6874i 0.0000 + 1.0000i 0.2003 - 0.9797i 0.6874 + 0.7263i -0.7418 + 0.6706i 0.8611 - 0.5084i -0.0779 + 0.9970i -0.9821 + 0.1883i 0.9999 + 0.0122i -0.5839 + 0.8118i -1.0000 + 0.0000i 0.5084 + 0.8611i -0.8118 - 0.5839i -0.6706 - 0.7418i -0.2978 + 0.9546i -0.1113 - 0.9938i -0.1883 - 0.9821i -0.7499 + 0.6615i 0.4205 - 0.9073i -0.0000 - 1.0000i -0.9546 - 0.2978i 0.9073 + 0.4205i 0.7418 - 0.6706i -0.4192 - 0.9079i 0.2964 + 0.9551i 0.9821 - 0.1883i 0.1127 - 0.9936i -0.2421 + 0.9702i 1.0000 - 0.0000i 0.9079 - 0.4192i -0.9702 - 0.2421i 0.6706 + 0.7418i 0.9198 + 0.3924i -0.4710 - 0.8821i 0.1883 + 0.9821i 0.5827 + 0.8127i 0.0551 - 0.9985i 0.0000 + 1.0000i -0.3924 + 0.9198i 0.9985 + 0.0551i -0.7418 + 0.6706i -0.9455 + 0.3257i 0.6287 + 0.7776i -0.9821 + 0.1883i -0.9772 - 0.2122i 0.1340 + 0.9910i -1.0000 + 0.0000i -0.3257 - 0.9455i -0.9910 + 0.1340i -0.6706 - 0.7418i 0.4830 - 0.8756i -0.7639 - 0.6453i -0.1883 - 0.9821i 0.8672 - 0.4979i -0.3182 - 0.9480i -1.0000 + 0.0000i -1.0000 + 0.0000i -1.0000 + 0.0000i 0.1006 - 0.9949i 0.1006 - 0.9949i 0.1006 - 0.9949i 0.9291 - 0.3699i 0.9291 - 0.3699i 0.9291 - 0.3699i -0.0000 - 1.0000i 0.7418 - 0.6706i 0.9821 - 0.1883i 0.9949 + 0.1006i 0.5925 + 0.8056i 0.0885 + 0.9961i 0.3699 + 0.9291i -0.4412 + 0.8974i -0.8428 + 0.5383i 1.0000 - 0.0000i -0.1006 + 0.9949i -0.9291 + 0.3699i -0.1006 + 0.9949i -0.9797 - 0.2003i -0.2745 - 0.9616i -0.9291 + 0.3699i -0.2745 - 0.9616i 0.7263 - 0.6874i 0.0000 + 1.0000i -0.5925 - 0.8056i 0.8428 - 0.5383i -0.9949 - 0.1006i 0.8611 - 0.5084i 0.4507 + 0.8927i -0.3699 - 0.9291i 0.8485 + 0.5292i -0.5839 + 0.8118i -1.0000 + 0.0000i 0.9797 + 0.2003i -0.7263 + 0.6874i 0.1006 - 0.9949i -0.2978 + 0.9546i -0.6108 - 0.7918i 0.9291 - 0.3699i -0.9843 + 0.1764i 0.4205 - 0.9073i -0.0000 - 1.0000i -0.8611 + 0.5084i 0.5839 - 0.8118i 0.9949 + 0.1006i -0.4192 - 0.9079i 0.7490 + 0.6626i 0.3699 + 0.9291i 0.6119 - 0.7909i -0.2421 + 0.9702i 1.0000 - 0.0000i 0.2978 - 0.9546i -0.4205 + 0.9073i -0.1006 + 0.9949i 0.9198 + 0.3924i -0.8604 - 0.5097i -0.9291 + 0.3699i 0.0764 + 0.9971i 0.0551 - 0.9985i 0.0000 + 1.0000i 0.4192 + 0.9079i 0.2421 - 0.9702i -0.9949 - 0.1006i -0.9455 + 0.3257i 0.9409 + 0.3386i -0.3699 - 0.9291i -0.7253 - 0.6884i 0.1340 + 0.9910i -1.0000 + 0.0000i -0.9198 - 0.3924i -0.0551 + 0.9985i 0.1006 - 0.9949i 0.4830 - 0.8756i -0.9879 - 0.1553i 0.9291 - 0.3699i 0.9997 + 0.0243i -0.3182 - 0.9480i -0.0000 - 1.0000i 0.9455 - 0.3257i -0.1340 - 0.9910i 0.9949 + 0.1006i 0.2289 + 0.9735i 0.9994 - 0.0335i 0.3699 + 0.9291i -0.7579 + 0.6523i 0.4910 + 0.8711i -0.0000 - 1.0000i -0.0000 - 1.0000i -0.0000 - 1.0000i 0.5925 + 0.8056i 0.5925 + 0.8056i 0.5925 + 0.8056i -0.8428 + 0.5383i -0.8428 + 0.5383i -0.8428 + 0.5383i 1.0000 - 0.0000i 0.6706 + 0.7418i 0.1883 + 0.9821i -0.8056 + 0.5925i -0.9797 - 0.2003i -0.7336 - 0.6796i -0.5383 - 0.8428i 0.2642 - 0.9645i 0.7263 - 0.6874i 0.0000 + 1.0000i -0.9949 - 0.1006i -0.3699 - 0.9291i -0.5925 - 0.8056i 0.8611 - 0.5084i 0.8485 + 0.5292i 0.8428 - 0.5383i 0.4507 + 0.8927i -0.5839 + 0.8118i -1.0000 + 0.0000i 0.8056 - 0.5925i 0.5383 + 0.8428i 0.8056 - 0.5925i -0.2978 + 0.9546i -0.9330 - 0.3600i 0.5383 + 0.8428i -0.9330 - 0.3600i 0.4205 - 0.9073i -0.0000 - 1.0000i -0.2003 + 0.9797i -0.6874 - 0.7263i 0.5925 + 0.8056i -0.4192 - 0.9079i 0.9841 + 0.1778i -0.8428 + 0.5383i 0.9335 - 0.3586i -0.2421 + 0.9702i 1.0000 - 0.0000i -0.5084 - 0.8611i 0.8118 + 0.5839i -0.8056 + 0.5925i 0.9198 + 0.3924i -0.9999 + 0.0107i -0.5383 - 0.8428i -0.4520 + 0.8920i 0.0551 - 0.9985i 0.0000 + 1.0000i 0.9546 + 0.2978i -0.9073 - 0.4205i -0.5925 - 0.8056i -0.9455 + 0.3257i 0.9800 - 0.1988i 0.8428 - 0.5383i -0.2628 - 0.9648i 0.1340 + 0.9910i -1.0000 + 0.0000i -0.9079 + 0.4192i 0.9702 + 0.2421i 0.8056 - 0.5925i 0.4830 - 0.8756i -0.9251 + 0.3798i 0.5383 + 0.8428i 0.8420 + 0.5395i -0.3182 - 0.9480i -0.0000 - 1.0000i 0.3924 - 0.9198i -0.9985 - 0.0551i 0.5925 + 0.8056i 0.2289 + 0.9735i 0.8370 - 0.5473i -0.8428 + 0.5383i -0.9864 + 0.1644i 0.4910 + 0.8711i 1.0000 - 0.0000i 0.3257 + 0.9455i 0.9910 - 0.1340i -0.8056 + 0.5925i -0.8226 - 0.5686i -0.7189 + 0.6951i -0.5383 - 0.8428i 0.6215 - 0.7834i -0.6463 - 0.7631i
size(C)
ans = 1×2
40 9
Sadiq Akbar
Sadiq Akbar 2021년 10월 19일
Thank you dear Cris LaPierre for your response. No you didn't take my point. I was saying that I want to make the response of the 1st code like that of 2nd. You tried but that is not according to my question. I wanted to make the response of 1st code like that of 2nd and I did that myself with several trial and errors. Thank you once again

댓글을 달려면 로그인하십시오.

카테고리

Help Center 및 File Exchange에서 Regression Tree Ensembles에 대해 자세히 알아보기

태그

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!

Translated by