Literature DB >> 2461128

The fractal random telegraph signal: signal analysis and applications.

L S Liebovitch1.   

Abstract

A random telegraph signal is a time series whose value S (t) at time t is either one of only two possible values. Many processes including chemical reactions, cell membrane ion channels, and electronic noise generate such signals. Usually, Markov models have been used to model and analyze such data. Instead, we present a new fractal random telegraph signal that is statistically self-similar in time. We show how to analyze such signals and apply those techniques to study burst noise in a defective operational amplifier and ion currents recorded through individual ion channels in a cell membrane.

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Year:  1988        PMID: 2461128     DOI: 10.1007/bf02368011

Source DB:  PubMed          Journal:  Ann Biomed Eng        ISSN: 0090-6964            Impact factor:   3.934


  9 in total

1.  Shelved optical electron amplifier: Observation of quantum jumps.

Authors: 
Journal:  Phys Rev Lett       Date:  1986-06-30       Impact factor: 9.161

2.  Characterization of fat fractals in nonlinear dynamical systems.

Authors: 
Journal:  Phys Rev Lett       Date:  1986-11-10       Impact factor: 9.161

3.  Observation of quantum jumps in a single atom.

Authors: 
Journal:  Phys Rev Lett       Date:  1986-10-06       Impact factor: 9.161

4.  Observation of quantum jumps.

Authors: 
Journal:  Phys Rev Lett       Date:  1986-10-06       Impact factor: 9.161

5.  Laser spectroscopy of trapped atomic ions.

Authors:  W M Itano; J C Bergquist; D J Wineland
Journal:  Science       Date:  1987-08-07       Impact factor: 47.728

6.  Fractal model of ion-channel kinetics.

Authors:  L S Liebovitch; J Fischbarg; J P Koniarek; I Todorova; M Wang
Journal:  Biochim Biophys Acta       Date:  1987-01-26

7.  Correcting single channel data for missed events.

Authors:  A L Blatz; K L Magleby
Journal:  Biophys J       Date:  1986-05       Impact factor: 4.033

8.  Fractal analysis of a voltage-dependent potassium channel from cultured mouse hippocampal neurons.

Authors:  L S Liebovitch; J M Sullivan
Journal:  Biophys J       Date:  1987-12       Impact factor: 4.033

9.  Electrons in silicon microstructures.

Authors:  R E Howard; L D Jackel; P M Mankiewich; W J Skocpol
Journal:  Science       Date:  1986-01-24       Impact factor: 47.728

  9 in total
  3 in total

1.  Using fractals to understand the opening and closing of ion channels.

Authors:  L S Liebovitch; T I Tóth
Journal:  Ann Biomed Eng       Date:  1990       Impact factor: 3.934

2.  Gating of maxi channels observed from pseudo-phase portraits.

Authors:  Sean P Parsons; Jan D Huizinga
Journal:  Am J Physiol Cell Physiol       Date:  2013-01-02       Impact factor: 4.249

3.  Testing fractal and Markov models of ion channel kinetics.

Authors:  L S Liebovitch
Journal:  Biophys J       Date:  1989-02       Impact factor: 4.033

  3 in total

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