Classification of Multi-User Chirp Modulation Signals Using Wavelet Higher-Order-Statistics Features and Artificial Intelligence Techniques

ISSN Print: 1913-3715
ISSN Online: 1913-3723
www.scirp.net/journal/ijcns
E-mail: [email protected]

Citations

"Classification of Multi-User Chirp Modulation Signals Using Wavelet Higher-Order-Statistics Features and Artificial Intelligence Techniques"
written by Said E. El-Khamy, Hend A. Elsayed,
published by International Journal of Communications, Network and System Sciences, Vol.5 No.9, 2012

has been cited by the following article(s):

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[4]	Discriminative estimated cumulants-based automatic modulation classification over multipath fading channels
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[5]	Automatic modulation classification using different neural network and PCA combinations
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[7]	A Sparse Modulation Signal Bispectrum Analysis Method for Rolling Element Bearing Diagnosis
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[8]	The Recognition of Human Activities Under UWB Communication
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[9]	Classification of chaotic codes using fuzzy clustering techniques and higher-order statistics features
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[10]	Ultrasound image despeckling using singular value decomposition
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[11]	Target Detection and Classification by UWB Communication Signal Based on Third-Order Cumulants
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[1]	Discriminative estimated cumulants-based automatic modulation classification over multipath fading channels Telecommunication Systems, 2025 DOI:10.1007/s11235-025-01271-5

[2]	A Sparse Modulation Signal Bispectrum Analysis Method for Rolling Element Bearing Diagnosis Mathematical Problems in Engineering, 2018 DOI:10.1155/2018/2954094

[3]	Classification of chaotic codes using fuzzy clustering techniques and higher-order statistics features 2015 1st URSI Atlantic Radio Science Conference (URSI AT-RASC), 2015 DOI:10.1109/URSI-AT-RASC.2015.7302985

[4]	Ultrasound image despeckling using singular value decomposition 2015 IEEE Recent Advances in Intelligent Computational Systems (RAICS), 2015 DOI:10.1109/RAICS.2015.7488393