序列(Sequence)

單調序列 (Monotonic sequences)

  • 令 {sn} \lbrace s_n \rbrace 為實數序列。
  • 單調遞增序列(increasing sequence): sn≤sn+1s_n \leq s_{n+1}, ∀n∈N\forall n \in \mathbb{N}.
  • 單調遞減序列(decreasing seqeunce): sn≥sn+1s_n \geq s_{n+1}, ∀n∈N\forall n \in \mathbb{N}.

收斂序列 (Convergence sequences)

  • A sequence {pn}\lbrace p_n \rbrace in metric space (X,d)(X, d) is said to be converge in XX if there is a point p∈Xp \in X such that:

    • ∀ϵ>0\forall \epsilon > 0 ∃ n0∈N\exists \ n_0 \in \mathbb{N} ∋ d(pn,p)<ϵ\ni \ d(p_n, p) < \epsilon, ∀n≥n0\forall n \geq n_0.

    • 通常寫為 limn→∞pn=p\lim_{n \rightarrow \infty} p_n = p or pn→pp_n \rightarrow p.

    • 收斂可解釋為只要nn夠大,sequence與收斂值之間的差距可以任意小。

  • If {pn}\lbrace p_n \rbrace does not converge, it is said to diverge (發散) .

  • Sequence是否收斂,除了自身的特性外,還必須確認收斂點pp是否為metric space中的元素。

    • E.g. {1/n}\lbrace 1/n \rbrace在R\mathbb{R}會收斂到0,但在R+\mathbb{R}^+, with metric ρ(x,y)=∣x−y∣\rho(x,y)=\vert x-y \vert不收斂,因0∉R+ 0 \notin \mathbb{R}^+ .
  • Theorem: Let {pn}\lbrace p_n \rbrace be a sequence in a metric space XX., then

    • limn→∞pn=p∈X⇔\lim_{n \rightarrow \infty} p_n = p \in X \Leftrightarrow every neighborhood of pp contains all but finitely many of the terms of {pn}\lbrace p_n \rbrace.

    • (收斂的唯一性) Let p1,p2∈Xp_1, p_2 \in X, limn→∞pn=p1\lim_{n \rightarrow \infty} p_n = p_1 and limn→∞pn=p2\lim_{n \rightarrow \infty} p_n = p_2 then p1=p2p_1 = p_2.

    • (收斂序列必有界) If {pn}\lbrace p_n \rbrace converges, then {pn}\lbrace p_n \rbrace bounded.

    • If E⊂XE \subset X and pp is a limit point of EE then there is a sequence {pn}\lbrace p_n \rbrace in EE such that limn→∞pn=p\lim_{n \rightarrow \infty} p_n = p.

Sequence 運算

  • Let {sn}\lbrace s_n \rbrace and {tn}\lbrace t_n \rbrace are complex sequences, limn→∞sn=s\lim_{n \rightarrow \infty} s_n = s and limn→∞tn=t\lim_{n \rightarrow \infty} t_n = t then

    • limn→∞(sn+tn)=s+t\lim_{n \rightarrow \infty} (s_n + t_n ) = s+t.

    • ∀c∈C\forall c \in \mathbb{C}, limn→∞csn=cs\lim_{n \rightarrow \infty} cs_n = cs, limn→∞(c+sn)=c+s\lim_{n \rightarrow \infty} (c + s_n) = c + s.

    • limn→∞sntn=st\lim_{n \rightarrow \infty} s_n t_n = st.

    • limn→∞1n=1s\lim_{n \rightarrow \infty} \frac{1}{n} = \frac{1}{s} if sn≠0 ∀ns_n \neq 0 \ \forall n and s≠0s \neq 0.

Subsequence

  • Subsequence為sequence中不連續的元素(但順序不變)所形成的序列,與演算法中subsequence定義相同。

  • Definition

    • Given a sequence {pn}\lbrace p_n \rbrace, consider a sequence {nk}\lbrace n_k \rbrace of positive integers such that n1<n2<⋯<nk<⋯ n_1 < n_2 < \cdots < n_k < \cdots then the sequence {pnk}\lbrace p_{n_k} \rbrace is called subsequence of {pn}\lbrace p_n \rbrace.
  • If limn→∞pn=p\lim_{n \rightarrow \infty} p_n = p ⇔\Leftrightarrow every subsequence of {pn}\lbrace p_n \rbrace converges to pp.

  • Theorem: If {pn}\lbrace p_n \rbrace is a sequence in a compact metric space (X,d)(X, d), then some subsequence of {pn}\lbrace p_n \rbrace converges to a point of XX.

Cauchy sequence

  • Definition

    • A sequence {pn}\lbrace p_n \rbrace in m a metric space (X,d)(X, d) is said to be a Cauchy sequence if ∀ϵ>0\forall \epsilon > 0 ∃n0∈N\exists n_0 \in \mathbb{N} ∋d(d(pn,pm)<ϵ\ni d(d(p_n, p_m) < \epsilon, ∀n,m>n0\forall n, m > n_0.

    • Cauchy sequence可用於判定sequence的收斂性,而不需要知道sequence收斂之值為何。

  • E.g. Rn ∀n\mathbb{R}^n \ \forall n are complete metric spaces, 所有的Cauchy sequences均收斂。

    • Converge sequence ⇒\Rightarrow Cauchy sequence。反之不一定成立,必須要加上compact metric space XX的條件以保證收斂值位於metric space中。
  • Properties:

    • E⊂XE \subset X is called bounded set if diamE<∞diamE < \infty.

    • If {pn}\lbrace p_n \rbrace is a sequence in XX and ENE_N consists of the points pN,pN+1,pN+2,⋯p_N, p_{N+1}, p_{N+2}, \cdots, then {pn}\lbrace p_n \rbrace is a Cauchy sequence ⇔\Leftrightarrow limN→∞diamEN=0\lim_{N \rightarrow \infty} diamE_N = 0.

    • If E¯\bar{E} is the closure of a set E⊂XE \subset X, then diamE¯=diamEdiam\bar{E} = diamE.

    • If knk_n is a sequence of compact sets in XX, kn⊃kn+1k_n \supset k_{n+1} ∀n∈N\forall n \in \mathbb{N}, and if limn→∞diamkn=0\lim_{n \rightarrow \infty} diam k_n =0, then ∩n=1∞kn\cap_{n=1}^{\infty}k_n conststs of exactly one point.

發散序列(Divergence sequence)

    • 定義: 發散序列( Divergence sequence)
    • 令 {sn}\lbrace s_n \rbrace 為實數序列且有以下性質:
    • (往正無窮大發散) ∀M∈R\forall M \in \mathbb{R} ∃n0∈N\exists n_0 \in \mathbb{N} ∋sn≥M\ni s_n \geq M ∀n≥n0\forall n \geq n_0. usually denoted as limn→∞sn→+∞\lim_{n \rightarrow \infty} s_n \rightarrow +\infty.
    • (往負無窮大發散) ∀M∈R\forall M \in \mathbb{R} ∃n0∈N\exists n_0 \in \mathbb{N} ∋sn≤M\ni s_n \leq M ∀n≥n0\forall n \geq n_0, usually denoted as limn→∞sn→−∞\lim_{n \rightarrow \infty} s_n \rightarrow -\infty.

序列的上極限

    • 定義: 序列的上極限(upper limit of sequence)
    • 令序列 {sn}\lbrace s_n \rbrace 有上界且 Mn=sup{sn,sn+1,sn+2,⋯,},M_n = \sup \lbrace s_n, s_{n+1}, s_{n+2}, \cdots,\rbrace, 則 Mn≥Mn+1≥Mn+2,⋯M_n \geq M_{n+1} \geq M_{n+2}, \cdots .
    • 若序列 MnM_n 收斂, 則序列 {sn}\lbrace s_n \rbrace 的上極限寫為 limsupn→∞sn=limn→∞Mn\lim \sup_{n \rightarrow \infty} s_n = \lim_{n \rightarrow \infty} M_n
    • .
    • 若序列 MnM_n 發散, 則序列的上極限也發散, limsupn→∞sn=∞\lim \sup_{n \rightarrow \infty} s_n = \infty.
    • 若序列 {sn}\lbrace s_n \rbrace 無上界,則序列的上極限發散, limsupn→∞sn=∞\lim \sup_{n \rightarrow \infty} s_n = \infty.
    • limsupn→∞sn=limn→∞(supm≥nsm)=infn≥0supk≥nsk=inf{sup{sk∣k≥n}∣n≥0} \lim \sup_{n \rightarrow \infty} s_n = \lim_{n \rightarrow \infty} \left( \sup_{m \geq n} s_m \right) = \inf_{n \geq 0} \sup_{ k \geq n} s_k = \inf \{ \sup\{ s_k| k \geq n \} | n \geq 0 \}

    • limsupn→∞sn=−liminfn→∞−sn \lim \sup_{n \rightarrow \infty} s_n = - \lim \inf_{n \rightarrow \infty} - s_n .
  • 令MM為序列{sn}\{s_n\}的上極限,則必須滿足以下兩個條件:

    • ∀ϵ>0 ∃n0∈N∋sn<M+ϵ ∀n≥n0\forall \epsilon > 0\ \exists n_0 \in \mathbb{N} \ni s_n < M + \epsilon \ \forall n \geq n_0 .
      • 此條件為序列極限有上界,但不唯一。
      • a,b∈R, a<b⇔∀ϵ>0, a<b+ϵa,b \in \mathbb{R},\ a < b \Leftrightarrow \forall \epsilon > 0,\ a < b+ \epsilon.
    • ∃ϵ>0 and n1∈N∋sn>M−ϵ ∀n≥n1 \exists \epsilon > 0 \text{ and } n_1 \in \mathbb{N} \ni s_n > M - \epsilon \ \forall n \geq n_1 .
      • 此條件為序列中有無窮多個元素(但非全部)落於M−ϵM-\epsilon的右側。
    • 滿足以上兩個條件時,寫為limsupn→∞s=M\lim \sup_{n \rightarrow \infty} s_ = M .
序列的上極限與下極限。
  • E.g. {sn}={(−1)n}\lbrace s_n \rbrace = \lbrace (-1)^n \rbrace,∀n∈N\forall n \in \mathbb{N},可知{sn}\lbrace s_n \rbrace在−1-1與11間振盪,所以limsupsn=1\lim \sup s_n = 1, and liminfsn=−1\lim \inf s_n = -1.

  • E.g. {sn}={−n}\lbrace s_n \rbrace = \lbrace -n \rbrace is bounded above, and ∀n∈N\forall n \in \mathbb{N}, Mn=−nM_n = -n, ∴limsupn→∞sn=−∞\therefore \lim \sup_{n \rightarrow \infty} s_n = -\infty.

數列的下極限

    • 定義: 序列的下極限(lower limit of sequence)
  • 令新列 {sn}\lbrace s_n \rbrace 有下界, 且 mn=inf{sn,sn+1,sn+2,⋯,}m_n = \inf \lbrace s_n, s_{n+1}, s_{n+2}, \cdots, \rbrace 則 mn≤mn+1≤mn+2,⋯m_n \leq m_{n+1} \leq m_{n+2}, \cdots .
  • 若序列 mnm_n 收斂,則序列 sns_n 的下極限寫為 liminfn→∞sn=limn→∞mn\lim \inf_{n \rightarrow \infty} s_n = \lim_{n \rightarrow \infty} m_n.
  • 若序列 mnm_n 發散,則序列的下極限也發散, liminfn→∞sn=∞\lim \inf_{n \rightarrow \infty} s_n = \infty.
  • 若序列 {sn}\lbrace s_n \rbrace 無下界, 則序列的下極限也發散 liminfn→∞sn=−∞\lim \inf_{n \rightarrow \infty} s_n = -\infty.
  • liminfn→∞sn=limn→∞(infm≥nsm)=supn≥0infk≥nsk=sup{inf{sk∣k≥n}∣n≥0} \lim \inf_{n \rightarrow \infty} s_n = \lim_{n \rightarrow \infty} \left( \inf_{m \geq n} s_m \right) = \sup_{n \geq 0} \inf_{k \geq n} s_k = \sup\{ \inf\{ s_k| k \geq n \} | n \geq 0 \}
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    • E.g. liminfn→∞(−1)n=−1 \lim \inf_{n \rightarrow \infty }(-1)^n = -1.

    • E.g. liminfn→∞n=∞\lim \inf_{n \rightarrow \infty} n = \infty.

    • E.g. liminfn→∞(−n)=−∞\lim \inf_{n \rightarrow \infty} (-n) = -\infty.

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