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Simple proofs and extensions of a result of L. D. Pustylnikov on the nonautonomous Siegel theorem

机译:L. D.Pustylnikov的简单证据和扩展缺乏神经统计学定理

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AbstractWe present simple proofs of a result of L.D. Pustylnikov extending to nonautonomous dynamics the Siegel theorem of linearization of analytic mappings. We show that if a sequencefnof analytic mappings ofCdhas a common fixed pointfn(0) = 0, and the mapsfnconverge to a linear mappingA∞ so fast that$$sumlimits_n {{{left| {{f_m} - {A_infty }} ight|}_{Linfty left( B ight)}} < infty } $$nfm?AL(B)/mo>$${A_infty } = diagleft( {{e^{2pi i{omega _1}}},...,{e^{2pi i{omega _d}}}} ight)omega = left( {{omega _1},...,{omega _q}} ight) in {mathbb{R}^d},$$A=diag(e2πiω1,...,e2πiωd)ω=(ω1,...,ωq)?d,thenfnis nonautonomously conjugate to the linearization. That is, there exists a sequencehnof analytic mappings fixing the origin satisfying$${h_{n + 1}} circ {f_n} = {A_infty }{h_n}.$$hn+1?fn=Ahn.The key point of the result is that the functions hn are defined in a large domain and they are bounded. We show that$${sumolimits_n {left| {{h_n} - Id} ight|} _{Linfty (B)}} < infty .$$展开▼
机译:<![cdata [ <标题>抽象 ara>我们提出了l.d的结果的简单证明。 Pustylnikov延伸到非自主动态的分析映射线性化的Siegel定理。我们表明,如果序列<重点类型=“斜体”> f <重点类型=“italic”> <重点类型=“斜体”的分析映射的N > C D 具有常见的固定点<重点类型=“斜体”> F <重点类型=“斜体”> n (0)= 0,以及地图<重点类型=“斜体”> f n 收敛到线性映射<重点类型=“斜体”> a ∞这么快,即 $$ sum limits_n {{{ left | {{f_m} - {a_ infty}} |} _ {l idty left(b reventsource> σ n < MROW> F M ?< / mo> a < mi> l b / mo> <等式Id =“等分“> $$ {a_ idty} = viag left({{e ^ {2 pi i { oomega _1}},...,{e ^ {2 pi i { omega _d}}}}}}} oomega = left({ omega _1},...,{ ommega _q}} inte) in { mathbb {r} ^ d},$$ a = d i a < / mi> g e 2 π i ω 1 e 2 π i ω d ω = ω 1 ... ω q < / mi> d 然后<重点键入=“斜体”> f n 是非实用的缀合物与线性化。也就是说,存在一个序列<重点类型=“斜体”> h <下标> <重点类型=“斜体”>修复满足<等式ID的原点的分析映射的分析映射=“equc”> $$ {h_ {n + 1}} circ {f_n} = {a_ infty} {h_n}。$$ h n + 1 < / mn> α〜α≤ f n = h n 结果的关键点是函数hn在大域中定义,它们是界定的。我们显示<等式ID =“equd”> < arequationSource格式=“tex”> $$ { sum nolimits_n { left | {{h_n} - id} light |} _ {l infty(b)}}

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