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Yudi Zhou
Researcher at Texas A&M University
Publications - 5
Citations - 338
Yudi Zhou is an academic researcher from Texas A&M University. The author has contributed to research in topics: Optical performance monitoring & Modulation. The author has an hindex of 5, co-authored 5 publications receiving 267 citations. Previous affiliations of Yudi Zhou include Hong Kong Polytechnic University.
Papers
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Journal ArticleDOI
Modulation format identification in heterogeneous fiber-optic networks using artificial neural networks.
TL;DR: Results of numerical simulations demonstrate that the proposed technique can effectively classify all these widely-used modulation formats with an overall estimation accuracy of 99.6% and also in the presence of various link impairments.
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Simultaneous optical performance monitoring and modulation format/bit-rate identification using principal component analysis
TL;DR: A novel technique for simultaneous multi-impairment monitoring and autonomous bit-rate and modulation format identification (BR-MFI) in next-generation heterogeneous fiber-optic communication networks is proposed by using principal component analysis-based pattern recognition on asynchronous delay-tap plots.
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Optical Performance Monitoring Using Artificial Neural Networks Trained With Empirical Moments of Asynchronously Sampled Signal Amplitudes
TL;DR: This work proposes a low-cost technique for simultaneous and independent optical signal-to-noise ratio (OSNR), chromatic dispersion, and polarization-mode dispersion monitoring in 40/56-Gb/s return- to-zero differential quadrature phase-shift keying and RZ-DQPSK systems.
Journal ArticleDOI
Non-data-aided joint bit-rate and modulation format identification for next-generation heterogeneous optical networks
TL;DR: This technique utilizes an artificial neural network in conjunction with asynchronous delay-tap plots to enable low-cost joint BR-MFI at the receivers as well as at the intermediate network nodes without requiring any prior information from the transmitters.
Journal ArticleDOI
Automatic modulation format/bit-rate classification and signal-to-noise ratio estimation using asynchronous delay-tap sampling
Faisal Nadeem Khan,Chiew Hoon Teow,Shiu Guong Kiu,Ming Chieng Tan,Yudi Zhou,Waled Hussein Al-Arashi,Alan Pak Tao Lau,Chao Lu +7 more
TL;DR: A novel technique for automatic classification of modulation formats/bit-rates of digitally modulated signals as well as non-data-aided (NDA) estimation of signal-to-noise ratio (SNR) in wireless networks is proposed.