Differentiation of linearly correlated noise from chaos in a biologic system using surrogate data

1992 ◽  
Vol 67 (5) ◽  
pp. 387-393 ◽  
Author(s):  
Steven J. Schiff ◽  
Taeun Chang
Keyword(s):  
Surrogate Data ◽  
Correlated Noise ◽  
Biologic System

TESTING FOR NONLINEARITY OF THE CONTRACTION SEGMENTS IN UTERINE ELECTROMYOGRAPHY

2000 ◽  
Vol 10 (12) ◽  
pp. 2785-2790 ◽  
Author(s):  
N. RADHAKRISHNAN ◽  
JAMES D. WILSON ◽  
CURTIS LOWERY ◽  
PAM MURPHY ◽  
HARI ESWARAN
Keyword(s):  
Fourier Transform ◽  
Null Hypothesis ◽  
Uterine Contraction ◽  
Nonlinear Function ◽  
Nonlinear Process ◽  
Surrogate Data ◽  
Correlated Noise ◽  
Uterine Contractility ◽  
Parametric Testing ◽  
Uterine Electromyography

In this report, we test for possible nonlinearity of the contraction segments interspersed in a uterine electromyography (EMG), recorded externally with abdominal electrodes. There have been several reports in which the uterine contractility had been assumed to be an auto-regressive process and others have hypothesized it as a nonlinear process and possibly chaotic. The surrogate data testing was used successfully to detect nonlinear behavior of physiological systems. However, there have been case studies, which discuss spurious identification of nonrandom structures. The proper choice of the null hypothesis and discriminant statistics plays a crucial role in the surrogate data testing. We have chosen the approximate entropy as the discriminant statistic for our tests. The null hypothesis addressed here is that the uterine contraction is a linearly correlated noise transformed by a nonlinear function. We applied the Amplitude Adjusted Fourier Transform (AAFT) and the Iterated Amplitude Adjusted Fourier Transform (IAAFT) tests to the uterine contraction data. The Kolmogorov Smirnov (D) statistics identified the discriminant values of the surrogates to be from a Gaussian distribution. Parametric testing showed a very low significance value, (~2σ), which indicated the absence of nonrandom structure in the contraction segment.

Correlated Noise Reduction for Electromagnetic Analysis

2013 ◽  
Vol E96.A (1) ◽  
pp. 185-195 ◽  
Author(s):  
Hongying LIU ◽  
Xin JIN ◽  
Yukiyasu TSUNOO ◽  
Satoshi GOTO
Keyword(s):  
Noise Reduction ◽  
Electromagnetic Analysis ◽  
Correlated Noise

AUTOMATIC ESTIMATION OF SPATIALLY CORRELATED NOISE VARIANCE IN SPECTRAL DOMAIN FOR IMAGES

2014 ◽  
Vol 73 (6) ◽  
pp. 511-527 ◽  
Author(s):  
V.V. Abramova ◽  
S. K. Abramov ◽  
V. V. Lukin ◽  
A. A. Roenko ◽  
Benoit Vozel
Keyword(s):  
Spectral Domain ◽  
Correlated Noise ◽  
Noise Variance ◽  
Spatially Correlated ◽  
Automatic Estimation ◽  
Spatially Correlated Noise

scholarly journals Fast radio burst detection in the presence of coloured noise

2021 ◽  
Vol 503 (4) ◽  
pp. 5223-5231
Author(s):  
C F Zhang ◽  
J W Xu ◽  
Y P Men ◽  
X H Deng ◽  
Heng Xu ◽  
...  
Keyword(s):  
False Alarm ◽  
Radio Burst ◽  
Pulse Width ◽  
False Alarm Probability ◽  
False Positives ◽  
Parameter Distribution ◽  
Correlated Noise ◽  
Width Distribution ◽  
Fast Radio Burst ◽  
The Impact

ABSTRACT In this paper, we investigate the impact of correlated noise on fast radio burst (FRB) searching. We found that (1) the correlated noise significantly increases the false alarm probability; (2) the signal-to-noise ratios (S/N) of the false positives become higher; (3) the correlated noise also affects the pulse width distribution of false positives, and there will be more false positives with wider pulse width. We use 55-h observation for M82 galaxy carried out at Nanshan 26m radio telescope to demonstrate the application of the correlated noise modelling. The number of candidates and parameter distribution of the false positives can be reproduced with the modelling of correlated noise. We will also discuss a low S/N candidate detected in the observation, for which we demonstrate the method to evaluate the false alarm probability in the presence of correlated noise. Possible origins of the candidate are discussed, where two possible pictures, an M82-harboured giant pulse and a cosmological FRB, are both compatible with the observation.

scholarly journals Forgery Detection in Digital Images by Multi-Scale Noise Estimation

2021 ◽  
Vol 7 (7) ◽  
pp. 119
Author(s):  
Marina Gardella ◽  
Pablo Musé ◽  
Jean-Michel Morel ◽  
Miguel Colom
Keyword(s):  
Noise Model ◽  
Correlated Noise ◽  
Forgery Detection ◽  
Color Channel ◽  
Image Block ◽  
Multi Scale ◽  
Compressed Images ◽  
Inconsistency Analysis ◽  
Highly Correlated ◽  
The Moment

A complex processing chain is applied from the moment a raw image is acquired until the final image is obtained. This process transforms the originally Poisson-distributed noise into a complex noise model. Noise inconsistency analysis is a rich source for forgery detection, as forged regions have likely undergone a different processing pipeline or out-camera processing. We propose a multi-scale approach, which is shown to be suitable for analyzing the highly correlated noise present in JPEG-compressed images. We estimate a noise curve for each image block, in each color channel and at each scale. We then compare each noise curve to its corresponding noise curve obtained from the whole image by counting the percentage of bins of the local noise curve that are below the global one. This procedure yields crucial detection cues since many forgeries create a local noise deficit. Our method is shown to be competitive with the state of the art. It outperforms all other methods when evaluated using the MCC score, or on forged regions large enough and for colorization attacks, regardless of the evaluation metric.

scholarly journals Modifications in the Topological Structure of EEG Functional Connectivity Networks during Listening Tonal and Atonal Concert Music in Musicians and Non-Musicians

2021 ◽  
Vol 11 (2) ◽  
pp. 159
Author(s):  
Almudena González ◽  
Manuel Santapau ◽  
Antoni Gamundí ◽  
Ernesto Pereda ◽  
Julián J. González
Keyword(s):  
Topological Structure ◽  
Phase Synchronization ◽  
Random Network ◽  
Small World ◽  
Surrogate Data ◽  
Musical Structure ◽  
Beta Band ◽  
Tonal Music ◽  
Frequency Bands ◽  
Concert Music

The present work aims to demonstrate the hypothesis that atonal music modifies the topological structure of electroencephalographic (EEG) connectivity networks in relation to tonal music. To this, EEG monopolar records were taken in musicians and non-musicians while listening to tonal, atonal, and pink noise sound excerpts. EEG functional connectivities (FC) among channels assessed by a phase synchronization index previously thresholded using surrogate data test were computed. Sound effects, on the topological structure of graph-based networks assembled with the EEG-FCs at different frequency-bands, were analyzed throughout graph metric and network-based statistic (NBS). Local and global efficiency normalized (vs. random-network) measurements (NLE|NGE) assessing network information exchanges were able to discriminate both music styles irrespective of groups and frequency-bands. During tonal audition, NLE and NGE values in the beta-band network get close to that of a small-world network, while during atonal and even more during noise its structure moved away from small-world. These effects were attributed to the different timbre characteristics (sounds spectral centroid and entropy) and different musical structure. Results from networks topographic maps for strength and NLE of the nodes, and for FC subnets obtained from the NBS, allowed discriminating the musical styles and verifying the different strength, NLE, and FC of musicians compared to non-musicians.

scholarly journals Escape dynamics of active particles in multistable potentials

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
A. Militaru ◽  
M. Innerbichler ◽  
M. Frimmer ◽  
F. Tebbenjohanns ◽  
L. Novotny ◽  
...  
Keyword(s):  
Transition State Theory ◽  
Silica Nanoparticle ◽  
State Theory ◽  
Biological Processes ◽  
Correlated Noise ◽  
Stochastic Force ◽  
Escape Dynamics ◽  
Active Particles ◽  
Bistable Potential ◽  
Quantitative Understanding

AbstractRare transitions between long-lived metastable states underlie a great variety of physical, chemical and biological processes. Our quantitative understanding of reactive mechanisms has been driven forward by the insights of transition state theory and in particular by Kramers’ dynamical framework. Its predictions, however, do not apply to systems that feature non-conservative forces or correlated noise histories. An important class of such systems are active particles, prominent in both biology and nanotechnology. Here, we study the active escape dynamics of a silica nanoparticle trapped in a bistable potential. We introduce activity by applying an engineered stochastic force that emulates self-propulsion. Our experiments, supported by a theoretical analysis, reveal the existence of an optimal correlation time that maximises the transition rate. We discuss the origins of this active turnover, reminiscent of the much celebrated Kramers turnover. Our work establishes a versatile experimental platform to study single particle dynamics in non-equilibrium settings.

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