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📁 an analysis software with souce code for the time series with methods based on the theory of nonline
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12 
   Phys. Rev. Lett. <B>76</B>, 4705 (1996).
<P>
<DT><A NAME="schmelcher"><STRONG>50</STRONG></A><DD>
P. Schmelcher, and F.&nbsp;K. Diakonos,
   <EM>A general approach to the finding of unstable periodic orbits in
   chaotic dynamical systems</EM>,
   Physical Review E <B>57</B>, 2739 (1998).
<P>
<DT><A NAME="kugiLL"><STRONG>51</STRONG></A><DD>
D. Kugiumtzis, O.&nbsp;C. Lingj&#230;rde, and N. Christophersen,
   <EM>Regularized local linear prediction of chaotic time series</EM>,
   Physica D 112 (1998) 344.
<P>
<DT><A NAME="jaeger"><STRONG>52</STRONG></A><DD>
L. Jaeger and H. Kantz,
   <EM><a href="../../../../../tppmsgs/msgs0.htm#30" tppabs="http://www.mpipks-dresden.mpg.de/publ/year95/9510004/9510004.ps.gz">Unbiased reconstruction of the dynamics underlying a noisy chaotic time
   series</a></EM>, 
   CHAOS 6 (1996) 440.
<P>
<DT><a name="casdagli91"><A NAME="Casdagli_royal"><STRONG>53</STRONG></A><DD> 
M. Casdagli,
   <EM>Chaos and deterministic versus stochastic nonlinear modeling</EM>,
   J. Roy. Stat. Soc. <B>54</B>, 303 (1991).
<P>
<DT><A NAME="rbf"><STRONG>54</STRONG></A><DD>    D. Broomhead and D. Lowe,
   <EM>Multivariable functional interpolation and adaptive networks</EM>,
   Complex Syst. <B>2</B>, 321 (1988).
<P>
<DT><A NAME="lenny_rbf"><STRONG>55</STRONG></A><DD>
L.&nbsp;A. Smith,
   <EM>Identification and prediction of low dimensional dynamics</EM>,
   Physica D <B>58</B>, 50 (1992).
<P>
<DT><A NAME="Casdagli_pred"><STRONG>56</STRONG></A><DD>
M. Casdagli,
   <EM>Nonlinear prediction of chaotic time series</EM>,
   Physica D <B>35</B>, 335 (1989); Reprinted in&nbsp;[<A HREF="citation.html#coping" tppabs="http://www.mpipks-dresden.mpg.de/~tisean/TISEAN_2.0/docs/chaospaper/citation.html#coping">9</A>].
<P>
<DT><A NAME="ks"><STRONG>57</STRONG></A><DD>  
E.&nbsp;J. Kostelich and T. Schreiber,
   <EM>Noise reduction in chaotic time series data: A survey of common
   methods</EM>,
   Phys. Rev. E <B>48</B>, 1752 (1993).
<P>
<DT><A NAME="Davies"><STRONG>58</STRONG></A><DD>
M.&nbsp;E. Davies,
   <EM>Noise reduction schemes for chaotic time series</EM>,
   Physica D <B>79</B>, 174 (1994).
<P>
<DT><A NAME="lazy"><STRONG>59</STRONG></A><DD>
T. Schreiber, 
   <EM>Extremely Simple Nonlinear Noise Reduction Method</EM>, 
   Phys. Rev. E <B>47</B>, 2401 (1993).
<P>
<DT><A NAME="b.dat"><STRONG>60</STRONG></A><DD>
D.&nbsp;R. Rigney, A.&nbsp;L. Goldberger, W. Ocasio, Y. Ichimaru,  G.&nbsp;B. Moody, and
   R. Mark, 
   <EM>Multi-channel physiological data: Description and analysis (Data set
   B)</EM>, 
   in&nbsp;[<A HREF="citation.html#SFI" tppabs="http://www.mpipks-dresden.mpg.de/~tisean/TISEAN_2.0/docs/chaospaper/citation.html#SFI">17</A>].
<P>
<DT><A NAME="on"><STRONG>61</STRONG></A><DD> 
P. Grassberger, R. Hegger, H. Kantz, C. Schaffrath, and
   T. Schreiber, 
   <EM>On noise reduction methods for chaotic data</EM>,
   CHAOS <B>3</B>, 127 (1993); Reprinted in&nbsp;[<A HREF="citation.html#coping" tppabs="http://www.mpipks-dresden.mpg.de/~tisean/TISEAN_2.0/docs/chaospaper/citation.html#coping">9</A>].
<P>
<DT><A NAME="buzug"><STRONG>62</STRONG></A><DD>
H. Kantz, T. Schreiber, I. Hoffmann, T. Buzug, G. Pfister, L.&nbsp;G.&nbsp;Flepp, 
   J.&nbsp;Simonet, R.&nbsp;Badii, and E. Brun,
   <EM>Nonlinear noise reduction: a case study on experimental data</EM>,
   Phys. Rev. E <B>48</B>, 1529 (1993).
<P>
<DT><A NAME="raser"><STRONG>63</STRONG></A><DD>
M. Finardi, L. Flepp, J. Parisi, R. Holzner, R. Badii, and E. Brun, 
   <EM>Topological and metric analysis of heteroclinic crises in laser chaos</EM>,
   Phys. Rev. Lett. <B>68</B>, 2989 (1992).
<P>
<DT><A NAME="danger"><STRONG>64</STRONG></A><DD>
A.&nbsp;I. Mees and K. Judd,
   <EM>Dangers of geometric filtering</EM>,
   Physica D <B>68</B> 427 (1993).
<P>
<DT><a name="filter"><A NAME="Filter"><STRONG>65</STRONG></A><DD>
T. Schreiber and M. Richter, 
   <EM><a href="../../../../../tppmsgs/msgs0.htm#31" tppabs="http://xxx.lanl.gov/abs/chao-dyn/9803008">Nonlinear projective
   filtering in a data stream</a></EM>, to appear in Int. J. Bifurcat. Chaos
 (1999).
<P>
<DT><A NAME="fetal2"><STRONG>66</STRONG></A><DD>
M. Richter, T. Schreiber, and D.&nbsp;T. Kaplan,
   <EM><a href="../../../../../tppmsgs/msgs0.htm#32" tppabs="http://www.theorie.physik.uni-wuppertal.de/Chaos/schreiber/myrefs/IEEE.ps.gz">Fetal ECG extraction with nonlinear phase space projections</a></EM>,
   IEEE Trans. Bio-Med. Eng. <B>45</B>, 133 (1998).
<P>
<DT><A NAME="EckRuelle"><STRONG>67</STRONG></A><DD>
J.-P. Eckmann and D. Ruelle, 
   <EM>Ergodic theory of chaos and strange attractors</EM>, 
   Rev. Mod. Phys. <B>57</B>, 617 (1985).
<P>
<DT><A NAME="spurious"><STRONG>68</STRONG></A><DD>
R. Stoop and J. Parisi,
   <EM>Calculation of Lyapunov exponents avoiding spurious elements</EM>,
   Physica D <B>50</B>, 89 (1991).
<P>
<DT><a name="holger"><A NAME="Holger"><STRONG>69</STRONG></A><DD> H. Kantz,
   <EM>A robust method to estimate the maximal Lyapunov exponent of a time
   series</EM>,
   Phys. Lett. A <B>185</B>, 77 (1994).
<P>
<DT><A NAME="rose"><STRONG>70</STRONG></A><DD>
M.&nbsp;T. Rosenstein, J.&nbsp;J. Collins, C.&nbsp;J. De&nbsp;Luca,
   <EM>A practical method for calculating largest Lyapunov exponents from 
   small data sets</EM>,
   Physica D <B>65</B>, 117 (1993).
<P>
<DT><a name="sasa"><A NAME="sano"><STRONG>71</STRONG></A><DD>
M. Sano and Y. Sawada, 
   <EM>Measurement of the Lyapunov spectrum from a chaotic time series</EM>,
   Phys. Rev. Lett. <B>55</B>, 1082 (1985).
<P>
<DT><A NAME="KaplanYorke"><STRONG>72</STRONG></A><DD>  J. Kaplan and J. Yorke
   <EM>Chaotic behavior of multidimensional difference equations</EM>
   In Peitgen, H.&nbsp;O. &amp; Walther, H.&nbsp;O., editors,
   ``Functional Differential Equations and Approximation of Fixed Points''
   Springer, New York (1987).
<P>
<DT><a name="gp"><A NAME="GP"><STRONG>73</STRONG></A><DD>
P. Grassberger and I. Procaccia, 
   Physica D <B>9</B>, 189 (1983).
<P>
<DT><A NAME="SauerYorke"><STRONG>74</STRONG></A><DD>
T. Sauer and J. Yorke,
   <EM>How many delay coordinates do you need?</EM>,
   Int. J. Bifurcation and Chaos <B>3</B>, 737 (1993).
<P>
<DT><A NAME="theiler_dim"><STRONG>75</STRONG></A><DD>
J. Theiler, 
   J. Opt. Soc. Amer. A <B>7</B>, 1055 (1990).
<P>
<DT><A NAME="dim"><STRONG>76</STRONG></A><DD>
H. Kantz and T. Schreiber,
   <em>Dimension estimates and physiological data</em>,
   CHAOS <B>5</B>, 143 (1995); Reprinted in&nbsp;[<A HREF="citation.html#dyndis" tppabs="http://www.mpipks-dresden.mpg.de/~tisean/TISEAN_2.0/docs/chaospaper/citation.html#dyndis">18</A>].
<P>
<DT><A NAME="grass_finite"><STRONG>77</STRONG></A><DD>
P. Grassberger, 
   <EM>Finite sample corrections to entropy and dimension estimates</EM>,
   Phys. Lett. A <B>128</B>, 369 (1988).
<P>
<DT><A NAME="takens_est"><STRONG>78</STRONG></A><DD>
F. Takens, 
   in: B.&nbsp;L.&nbsp;J. Braaksma, H.&nbsp;W. Broer, and F. Takens, eds.,
   ``Dynamical Systems and Bifurcations'', 
   Lecture Notes in Math. Vol.&nbsp;1125, Springer, Heidelberg (1985).
<P>
<DT><A NAME="takens_theiler"><STRONG>79</STRONG></A><DD> 
J. Theiler, 
   <EM>Lacunarity in a best estimator of fractal dimension</EM>,
   Phys. Lett. <B>A 135</B>, 195 (1988).
<P>
<DT><A NAME="ghez1"><STRONG>80</STRONG></A><DD> 
J.&nbsp;M. Ghez and S. Vaienti, 
   <EM>Integrated wavelets on fractal sets I: The correlation dimension</EM>,
   Nonlinearity <B>5</B>, 777 (1992).
<P>
<DT><A NAME="badiipoliti"><STRONG>81</STRONG></A><DD>
R. Badii and A. Politi
   <EM>Statistical description of chaotic attractors</EM>,
   J. Stat. Phys. <B>40</B>, 725 (1985).
<P>
<DT><A NAME="theiler1"><STRONG>82</STRONG></A><DD>
J. Theiler, S. Eubank, A. Longtin, B. Galdrikian, and J.&nbsp;D. Farmer, 
   <EM>Testing for nonlinearity in time series: The method of surrogate data</EM>,
   Physica D <B>58</B>, 77 (1992); Reprinted in&nbsp;[<A HREF="citation.html#coping" tppabs="http://www.mpipks-dresden.mpg.de/~tisean/TISEAN_2.0/docs/chaospaper/citation.html#coping">9</A>].
<P>
<DT><a name="surro"><A NAME="surrowe"><STRONG>83</STRONG></A><DD>
T. Schreiber and A. Schmitz,
   <EM><a href="../../../../../tppmsgs/msgs0.htm#17" tppabs="http://xxx.lanl.gov/abs/chao-dyn/9909041">Improved surrogate data for nonlinearity tests</a></EM>,
   Phys. Rev. Lett. <B>77</B>, 635 (1996).
<P>
<DT><A NAME="theiler_sfi"><STRONG>84</STRONG></A><DD>
J. Theiler, P.&nbsp;S. Linsay, and D.&nbsp;M. Rubin, 
   <EM><a href="../../../../../tppmsgs/msgs0.htm#33" tppabs="http://nis-www.lanl.gov/~jt/Papers/coherence-time.ps.gz">Detecting nonlinearity in data with long coherence times</a></EM>,
   in&nbsp;[<A HREF="citation.html#SFI" tppabs="http://www.mpipks-dresden.mpg.de/~tisean/TISEAN_2.0/docs/chaospaper/citation.html#SFI">17</A>].
<P>
<DT><a name="randomize"><A NAME="anneal"><STRONG>85</STRONG></A><DD>
T. Schreiber,
   <EM><a href="../../../../../tppmsgs/msgs0.htm#15" tppabs="http://xxx.lanl.gov/abs/chao-dyn/9909042">Constrained randomization of time series data</a></EM>,
   Phys. Rev. Lett. 80 (1998) 2105.
<P>
<DT><A NAME="BI"><STRONG>86</STRONG></A><DD>
T. Subba Rao and M.&nbsp;M. Gabr,
   ``An Introduction to Bispectral Analysis and Bilinear Time Series Models'',
   Lecture Notes in Statistics Vol.&nbsp;24, Springer, New York (1984).
<P>
<DT><A NAME="diks2"><STRONG>87</STRONG></A><DD> C. Diks, J.&nbsp;C. van Houwelingen, F. Takens, and J. DeGoede,
   <EM>Reversibility as a criterion for discriminating time series</EM>,
   Phys. Lett. A <B>201</B>, 221 (1995).
<P>
<DT><A NAME="power"><STRONG>88</STRONG></A><DD>
T. Schreiber and A. Schmitz,
   <EM><a href="../../../../../tppmsgs/msgs0.htm#34" tppabs="http://xxx.lanl.gov/abs/chao-dyn/9909043">Discrimination power of measures for nonlinearity in a time series</a></EM>,
   Phys. Rev. E <B>55</B>, 5443 (1997).
<P>
<DT><A NAME="Kadtke"><STRONG>89</STRONG></A><DD>
J. Kadtke,
   <EM>Classification of highly noisy signals using global dynamical models</EM>,
   Phys. Lett. A <B>203</B>, 196 (1995).
<P>
<DT><A NAME="B1"><STRONG>90</STRONG></A><DD>
R. Manuca and R. Savit,
   <EM>Stationarity and nonstationarity in time series analysis</EM>,
   Physica D <B>99</B>, 134 (1996).
<P>
<DT><A NAME="casEEG"><STRONG>91</STRONG></A><DD>
M.&nbsp;C. Casdagli, L.&nbsp;D. Iasemidis, R.&nbsp;S. Savit, R.&nbsp;L. Gilmore, S. Roper, and
   J.&nbsp;C. Sackellares,
   <EM>Non-linearity in invasive EEG recordings from patients with temporal
   lobe epilepsy</EM>,
   Electroencephalogr. Clin. Neurophysiol. <B>102</B>, 98 (1997).
<P>
<DT><A NAME="statio"><STRONG>92</STRONG></A><DD>
T. Schreiber,
   <EM><a href="../../../../../tppmsgs/msgs0.htm#35" tppabs="http://xxx.lanl.gov/abs/chao-dyn/9909044">Detecting and analysing nonstationarity in a time series using
   nonlinear cross predictions</a></EM>,
   Phys. Rev. Lett. <B>78</B>, 843 (1997).
<P>
<DT><A NAME="cawley"><STRONG>93</STRONG></A><DD>
R. Cawley and G.&nbsp;H. Hsu,
  <em>Local-geometric-projection method for noise reduction in chaotic maps 
   and flows</em>,
   Phys. Rev. A. <b>46</b>, 3057 (1992).
<P>
<DT><A NAME="kantz"><STRONG>94</STRONG></A><DD>
H. Kantz,
  <em>Quantifying the closeness of fractal measures</em>,
  Phys. Rev. E <b>49</b>, 5091 (1994).
<P>
<DT><A NAME="sauer"><STRONG>95</STRONG></A><DD>
T. Sauer,
  <em>A noise reduction method for signals from nonlinear
  systems</em>,
  Physica D <b>58</b>, 193 (1992).
<P>
<DT><A NAME="aurell97"><STRONG>96</STRONG></A><DD>
E. Aurell, G. Boffetta, A. Crisanti, G. Paladin, and A. Vulpiani,
   <em>Predictability in the large: an extension of the concept of
   Lyapunov exponent</em>,
   J. Phys. A <b>30</b>, 1 (1997).
<DT><A NAME="cluster"><STRONG>97</STRONG></A><DD>
T. Schreiber and A. Schmitz,
      <em> Classification of time series data with nonlinear similarity 
      measures</em>, 
      Phys. Rev. Lett. <b>79</b>, 1475 (1997).
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<P><ADDRESS>
<I>Thomas Schreiber <BR>
Wed Jan  6 15:38:27 CET 1999</I>
</ADDRESS>
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