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Lipsitz LA 《Chaos (Woodbury, N.Y.)》1995,5(1):102-109
Healthy physiologic control of cardiovascular function is a result of complex interactions between multiple regulatory processes that operate over different time scales. These include the sympathetic and parasympathetic nervous systems which regulate beat-to-beat heart rate (HR) and blood pressure (BP), as well as extravascular volume, body temperature, and sleep which influence HR and BP over the longer term. Interactions between these control systems generate highly variable fluctuations in continuous HR and BP signals. Techniques derived from nonlinear dynamics and chaos theory are now being adapted to quantify the dynamic behavior of physiologic time series and study their changes with age or disease. We have shown significant age-related changes in the 1/f(x) relationship between the log amplitude and log frequency of the heart rate power spectrum, as well as declines in approximate dimension and approximate entropy of both heart rate and blood pressure time series. These changes in the "complexity" of cardiovascular dynamics reflect the breakdown and decoupling of integrated physiologic regulatory systems with aging, and may signal an impairment in cardiovascular ability to adapt to external and internal perturbations. Studies are currently underway to determine whether the complexity of HR or BP time series can distinguish patients with fainting spells due to benign vasovagal reactions from those due to life-threatening cardiac arrhythmias. Thus, measures of the complexity of physiologic variability may provide novel methods to monitor cardiovascular aging and test the efficacy of specific interventions to improve adaptive capacity in old age. (c) 1995 American Institute of Physics. 相似文献
54.
LetX be a Brownian motion defined on the line (withX(0)=0) and letY be an independent Brownian motion defined on the nonnegative real numbers. For allt0, we define theiterated Brownian motion (IBM),Z, by setting
. In this paper we determine the exact uniform modulus of continuity of the process Z.Research supported by NSF grant DMS-9122242. 相似文献
55.
Armstrong TA Bettoni D Bharadwaj V Biino C Borreani G Broemmelsiek D Buzzo A Calabrese R Ceccucci A Cester R Church M Dalpiaz P Dalpiaz PF Dimitroyannis D Fabbri M Fast J Gianoli A Ginsburg CM Gollwitzer K Govi G Hahn A Hasan M Hsueh S Lewis R Luppi E Macrí M Majewska AM Mandelkern M Marchetto F Marinelli M Marques J Marsh W Martini M Masuzawa M Menichetti E Migliori A Mussa R Palestini S Pallavicini M Passaggio S Pastrone N Patrignani C Peoples J Petrucci F Pia MG Pordes S Rapidis P Ray R 《Physical review D: Particles and fields》1996,54(11):7067-7070
56.
Common supports as fixed points 总被引:1,自引:0,他引:1
A family S of sets in R
d
is sundered if for each way of choosing a point from rd+1 members of S, the chosen points form the vertex-set of an (r–1)-simplex. Bisztriczky proved that for each sundered family S of d convex bodies in R
d
, and for each partition (S
, S
), of S, there are exactly two hyperplanes each of which supports all the members of S and separates the members of S
from the members of S
. This note provides an alternate proof by obtaining each of the desired supports as (in effect) a fixed point of a continuous self-mapping of the cartesian product of the bodies. 相似文献
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Thomas M. Lewis 《Journal of Theoretical Probability》1993,6(2):209-230
LetX, X i ,i≥1, be a sequence of independent and identically distributed ? d -valued random vectors. LetS o=0 and \(S_n = \sum\nolimits_{i = 1}^n {X_i } \) forn≤1. Furthermore letY, Y(α), α∈? d , be independent and identically distributed ?-valued random variables, which are independent of theX i . Let \(Z_n = \sum\nolimits_{i = 0}^n {Y(S_i )} \) . We will call (Z n ) arandom walk in random scenery. In this paper, we consider the law of the iterated logarithm for random walk in random scenery where deterministic normalizers are utilized. For example, we show that if (S n ) is simple, symmetric random walk in the plane,E[Y]=0 andE[Y 2]=1, then $$\mathop {\overline {\lim } }\limits_{n \to \infty } \frac{{Z_n }}{{\sqrt {2n\log (n)\log (\log (n))} }} = \sqrt {\frac{2}{\pi }} a.s.$$ 相似文献
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