Data for Logistic Map–Based Dynamic Chaotic Signals in the Presence of AWGN

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Main Author: Kozlenko, Mykola
Format: Recurso digital
Language:English
Published: Zenodo 2025
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author Kozlenko, Mykola
author_facet Kozlenko, Mykola
contents <p>This dataset contains synthetic dynamic chaotic signals generated using the logistic map and corrupted by additive white Gaussian noise. The data are intended for research and benchmarking in chaos-based signal modeling, nonlinear dynamics analysis, and machine learning experiments under noisy conditions. Number of records: 100. Each signal (row) contains 4096 samples. Signal to Noise ratio S/N: -13 dB, Normalized Signal to Noise ratio Eb/N0: +20dB. Target column: "symbol". Label 0: signal generated with bifurcation parameter r = 3.70. Label 1: signal generated with r = 3.75.</p>
format Recurso digital
id zenodo_https___doi_org_10_5281_zenodo_18110884
institution Zenodo
language eng
publishDate 2025
publisher Zenodo
record_format zenodo
spellingShingle Data for Logistic Map–Based Dynamic Chaotic Signals in the Presence of AWGN
Kozlenko, Mykola
Dynamic chaos,
Demodulation
Logistic map
Chaotic signals
Nonlinear dynamics
Synthetic data
Signal modeling
Classification dataset
<p>This dataset contains synthetic dynamic chaotic signals generated using the logistic map and corrupted by additive white Gaussian noise. The data are intended for research and benchmarking in chaos-based signal modeling, nonlinear dynamics analysis, and machine learning experiments under noisy conditions. Number of records: 100. Each signal (row) contains 4096 samples. Signal to Noise ratio S/N: -13 dB, Normalized Signal to Noise ratio Eb/N0: +20dB. Target column: "symbol". Label 0: signal generated with bifurcation parameter r = 3.70. Label 1: signal generated with r = 3.75.</p>
title Data for Logistic Map–Based Dynamic Chaotic Signals in the Presence of AWGN
topic Dynamic chaos,
Demodulation
Logistic map
Chaotic signals
Nonlinear dynamics
Synthetic data
Signal modeling
Classification dataset
url https://doi.org/10.5281/zenodo.18110884