國立臺北科技大學112學年度碩士班招生考試
系所組別:電機工程系碩士班丁組
科目:線性代數
解答:(1) {A=[−122−3−13]b=[412]⇒{ATA=[6−11−1122]ATb=[−411]⇒[ATA∣ATb]=[6−11−4−112211]⇒rref([ATA∣ATb])=[103012]⇒an LS solution: ˆx=[32](2) Since Ax=b has no solution, we need a "best" solution ˆx such that dist(b,Aˆx)≤dist(b,Ax)解答:Let yi=(xi−xj), then yi is a non-zero N×1 vector.We have {||H(yi)||22=(Hyi)H(Hyi)=(yHiHH)(Hyi)||yi||22=yHiyi. Thenλ2maxxHx≥xHHHHx≥λ2minxHx⇒yHiHHHyi≥λ2minyHiyi⇒||H(yi)||22≥λ2min||yi||22⇒min||H(yi)||22≥λ2minmin||yi||22⇒minxi≠xj||H(xi−xj)||22≥λ2minminxi≠xj||(xi−xj)||22QED.
解答:(1) A:N x N matrix of the orthonormal eigenvectors of HHTB:diagonal matrix with r elements equal to the root of the positive eigenvalues of AAᵀC:transpose of an N x N matrix containing the orthonormal eigenvectors of AAT(2) If singular values are repeated, there will be more than one SVD. In this case, SVD is not unique.
解答:
解答:(1) Null(A):{x∣Ax=0,x∈Rn}(2) A0=0⇒0∈Null(A)Suppose u,v∈Null(A), then A(u+v)=A(u)+A(v)=0+0=0⇒u+v∈Null(A)Suppose u∈Null(A),A(cu)=cA(u)=c⋅0=0⇒cu∈Null(A),c is a scalarTherefore, Null(A) is a subspace(3) rank(A)+nullity(A)=N(4) A is not of full-rank ⇒rank(A)<N⇒dim(Col(A))<N⇒ the columns of A are linearly dependent.
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