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Dive into the research topics where Xiukai Ruan is active.

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Featured researches published by Xiukai Ruan.


Optics Express | 2014

Diffraction theory of high numerical aperture subwavelength circular binary phase Fresnel zone plate.

Yaoju Zhang; Hongchang An; Dong Zhang; Guihua Cui; Xiukai Ruan

An analytical model of vector formalism is proposed to investigate the diffraction of high numerical aperture subwavelength circular binary phase Fresnel zone plate (FZP). In the proposed model, the scattering on the FZPs surface, reflection and refraction within groove zones are considered and diffraction fields are calculated using the vector Rayleigh-Sommerfeld integral. The numerical results obtained by the proposed phase thick FZP (TFZP) model show a good agreement with those obtained by the finite-difference time-domain (FDTD) method within the effective extent of etch depth. The optimal etch depths predicted by both methods are approximately equal. The analytical TFZP model is very useful for designing a phase and hybrid amplitude-phase FZP with high-NA and short focal length.


Optics Express | 2016

Compact self-cascaded KTA-OPO for 2.6 μm laser generation

Yanmin Duan; Haiyong Zhu; Changwen Xu; Xiukai Ruan; Guihua Cui; Yaoju Zhang; Dingyuan Tang; Dianyuan Fan

We reported a compact self-cascaded KTA-OPO source for 2.6 μm coherent light generation. The OPO is driven in a diode end-pumped and Q-switched Nd:YVO4 laser cavity. Two OPO processes occurred in the same KTA crystal with non-critical phase matching. At an incident diode pump power of 8.7 W and a pulse repetition frequency of 60 kHz, the OPO can generate a maximum average output power of 445 mW at 2.59 μm. The slope efficiency was about 12.7%, and the power fluctuation was less than 8%. Therefore, the self-cascade OPO based on KTA offers a promise scheme for the rugged and compact mid-infrared 2.6 μm laser generation.


Optics Express | 2016

Accurate method for computing correlated color temperature

Guihua Cui; Manuel Melgosa; Xiukai Ruan; Yaoju Zhang; Long Ma; Kaida Xiao; M. Ronnier Luo

For the correlated color temperature (CCT) of a light source to be estimated, a nonlinear optimization problem must be solved. In all previous methods available to compute CCT, the objective function has only been approximated, and their predictions have achieved limited accuracy. For example, different unacceptable CCT values have been predicted for light sources located on the same isotemperature line. In this paper, we propose to compute CCT using the Newton method, which requires the first and second derivatives of the objective function. Following the current recommendation by the International Commission on Illumination (CIE) for the computation of tristimulus values (summations at 1 nm steps from 360 nm to 830 nm), the objective function and its first and second derivatives are explicitly given and used in our computations. Comprehensive tests demonstrate that the proposed method, together with an initial estimation of CCT using Robertsons method [J. Opt. Soc. Am. 58, 1528-1535 (1968)], gives highly accurate predictions below 0.0012 K for light sources with CCTs ranging from 500 K to 106 K.


Neural Computing and Applications | 2018

Direct sequence estimation: a functional network approach

Xiukai Ruan; Yanhua Tan; Guihua Cui; Wenbin Liu; Xiaojing Shi; Qibo Cai; Haitao Zhao

Functional networks (FNs) have shown excellent performance in probability, statistics, engineering applications, etc., but so far no methods of direct sequence estimation (DSE) for communication systems using FN have been published. The paper presents a new DSE approach using FN, which can be applied to cases with plural source signal sequence, short sequence or even the absence of training sequence. The proposed method can estimate the source sequence directly from the observed output data without training sequence and pre-estimating the channel impulse response. Firstly, a multiple-input multiple-output FN (MIMOFN), in which the initial input vector is devised via QR decomposition of receiving signal matrix, is adopted to solve the special issue. Meantime, a design method of the neural function for this special MIMOFN is proposed. Then, the learning rule for the parameters of neural functions is trained and updated by back-propagation learning algorithm. Finally, a simulation experiment is performed, the feasibility and accuracy of the method are showed from the experimental results, and some special simulation phenomena of the algorithm are observed.


international conference on optoelectronics and microelectronics | 2017

Signal detection for polarization multiplexing QAM optical coherent receivers using ESN

Yanhua Tan; Zhili Zhou; Xiukai Ruan; Yuxing Dai; Haiyong Zhu; Yaoju Zhang

Coherent optical systems face two main categories of linear impairments, chromatic dispersion (CD) and polarization mode dispersion (PMD). Both CD and PMD will create large inter-symbol interference (ISI). This paper focuses on M-quadrature amplitude modulation (QAM) signal detection directly using Echo State Networks (ESN) technique for compensating (residual CD and PMD) dispersion of coherent optical systems. The proposed approach can estimate directly the input sequence at the coherent receivers, without getting the electronic equalizer coefficients and estimating optical channel impulse response. In addition, the proposed approach can guarantee a convergence within a short data packet.


International Journal of Optics | 2017

Mid-infrared tunable intracavity singly resonant optical parametric oscillator based on Mgo : PPLN

Jing Zhang; Yongchang Zhang; Yanmin Duan; Xiukai Ruan; Hongyan Wang; Yaoju Zhang; Haiyong Zhu; Dingyuan Tang

In this paper, we demonstrated a continuous-wave intracavity singly resonant optical parametric oscillator based on periodically poled MgO:LiNbO3 (MgO:PPLN) pumped by a diode-pumped Nd:YVO4 laser at 1064 nm. The singly resonant optical parametric oscillator only outputs the idler light as its cavity high reflectivity was coated at the signal light. When the temperature was controlled at 120°C and the grating period set at 30.5 μm for the MgO:PPLN, a maximum idler output power of 1.27 W and central wavelength at 3251 nm were obtained under an incident diode pump power of 12.4 W, corresponding to the conversion efficiency of 10.2%. By changing the temperature and the grating period of MgO:PPLN crystal, widely tunable mid-infrared spectra from 2.95 to 4.16 μm were achieved.


IEEE Photonics Journal | 2017

Information Entropy and Fuzzy Logic Based Equalizer for PolMux QAM Coherent Optical Communication Systems

Zhili Zhou; Yiju Zhan; Qingling Cai; Xiukai Ruan; Guihua Cui; Yuxing Dai; Haiyong Zhu

In polarization-multiplexed (PolMux) coherent optical communication systems, adaptive blind equalizer is efficient in demultiplexing and mitigating intersymbol interference (ISI). A novel blind algorithm based on Information Entropy and fuzzy logic is proposed, in which the Renyis


Digital Signal Processing | 2017

Blind sequence detection using reservoir computing

Xiukai Ruan; Chang Li; Weibo Yang; Guihua Cui; Haiyong Zhu; Zhili Zhou; Yuxing Dai; Xiaojing Shi

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Archive | 2016

Direct Signal Detection Without Data‐Aided: A MIMO Functional Network Approach

Xiukai Ruan; Yanhua Tan; Yuxing Dai; Guihua Cui; Qibo Cai Xiaojing Shi; Chang Li; Han Li; Yaoju Zhang; Dameng Dai

entropy is adopted to measure the uncertainty of error between the desired and estimated probability density function (PDF). The nonparametric PDF estimator of Parzen window method is employed to estimate the PDF of symbols. Meantime, a fuzzy-logic tuning unit is designed to adjust the kernel size of Parzen window, which leads to fast convergence rate and small steady mean-square error. By simulation in PolMux-16 quadrature amplitude modulation (QAM) coherent systems, the correctness and effectiveness of the proposed algorithm are verified.


Optics Communications | 2017

A double-DD blind equalizer for PolMux QAM optical coherent systems

Zhili Zhou; Yiju Zhan; Xiukai Ruan; Qibo Cai; Guihua Cui; Guijun Zhu

Abstract The performance of M -ary quadrature amplitude modulation (QAM) can seriously be degraded by inter-symbol interference (ISI) as the number of levels increases. To mitigate ISI, blind sequence detection (BSD) has very important applications in data transmission systems, particularly where sending a training sequence is disruptive or costly. A new BSD approach of short data in QAM systems using reservoir computing (RC) is presented, together with the detailed theoretical derivation of the algorithm. Its convergence can be guaranteed within a short data packet and, therefore, it works in systems with a much shorter data record and faster time-varying channels. A RC network is constructed to solve the special issue of BSD, with reservoir weight matrix generated via the reduced QR decomposition from the view of receiving signal subspace instead of being selected randomly. The design methods of the activation function and readout function, the variation rule of initial vector which is changed by reservoir weight, and complexity of the proposed algorithm are described, respectively. The readout weight of the RC network is trained and updated by support vector regression (SVR) with a Gaussian insensitive loss function. The correctness and effectiveness of the new approach are verified by simulations, and some special simulation phenomena of the algorithm are discussed.

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Zhili Zhou

Sun Yat-sen University

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Dingyuan Tang

Nanyang Technological University

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