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無年度 - 主題課程_線性映射:one to one and onto#107850
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題組內容
106台聯大_工數A”B
(10%) Define a linear transformationT : R
3
→ R
3
by T((1,0,0)) =(0,1,0),T((, 1, 0)) - (0,0,1), and T((0,0, 1)) = (1,0,0).
(b) (5%) Is T : R
3
→ R
3
one-to-one and onto? Why or why not?
相關申論題
(a). Prove that if ker T= {0}; then T is one-to-one.(7 pts)
#462103
(b). Suppose T is one-to-one and {u1,... ,uk} is a linearly independent set of vectors in U. Prove that [T(u1),....,T(uk)] is a linearly independent set of vectors in V.(7 pts)
#462104
(c). Define UP(t)(a polynomil of degree 2 and its standard form is P(t) = a0+ a1t + a2t2),V R3, and T(U) = Find U such that the image under T of Uis [11, 1, -1]T. (7 pts)
#462105
(a) (5%) Find a vector u = (ux, uy, uz) such that T(u) - u and.
#462106
(12%) Let V be a finite-dimensional vector space and T :V →V be linear. Suppose rank(T) = rank(T2). Prove that R(T) ∩N(T) = {0}.
#467033
(13%) Given a vector space V over F. Define the dual space of V* of V as the set of all functions (also known as linear functionals) from V to F, i.e, V* {f|f : V →F}. It is obvious that V* is itself also a vector space with the addition + :V*'x V*→ V* and scalar multiplication * : F x V*→ V* defined as pointwise addition as well as pointwise scalar multiplication. Given any linear transformation T : V→ W. The transpose Tt is a linear transformation from W* to V* defined by Tt(f) = fT for any f W*. For every subset S of V, we define the annihilator Suppose V, W are both finite-dimensional vector spaces and T : V → W is linear. Prove that .N(Tt) = (R(T))0.
#467032
(10%) The nullities of the matrices BBT - λ/ for λ= 0, 1,2,3, 4 are______,________,_________,_______ respectively.
#467031
(d) (2%) Compute dim(N(Bt A)).
#467030
(c) (3%) Compute rank(AtAAAt).
#467029
(b) (2%) Compute rank(AB).
#467028
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