A high-sensitive fiber curvature sensor using twin core fiber-based filter

A high-sensitive fiber curvature sensor is proposed and experimentally demonstrated in a large measurement range by using a twin core fiber (TCF)-based filter as sensor head. Applying the coupled-mode theory and equivalent refractive index model, we theoretically anticipate the “blue shift” of the transmission dips of the TCF-based filter when sensor head is bent. Experimentally, we fabricate an 86.9 mm TCF-based filter with a free spectral range of 49 nm and characterize its curvature performance by measuring the wavelength shift. A nonlinear “blue shift” of the wavelength is observed when we increase the curvature. The relationship between wavelength shift and curvature is a second-order polynomial function. In the range from 0 to 9.30 m^?1, the maximum sensitivity is up to ?14.7 nm/m^?1. The measurement range can be further increased by selecting a shorter TCF.     

用于混沌时间序列自适应预测的一种少参数二阶Volterra滤波器

研究了二阶Volterra滤波器的一种乘积耦合近似实现结构及其非线性NLMS自适应算法,并用这种少参数二阶Volterra滤波器(RPSOVF)研究了一些混沌信号的非线性自适应预测性能.仿真研究结果表明:所给出的非线性NLMS自适应算法能够保证这种RPSOVF的稳定性和收敛性,且RPSOVF用这种非线性NLMS自适应算法能够自适应预测一些混沌时间序列. 关键词： 混沌 非线性自适应预测 Volterra滤波器 非线性NLMS自适应算法     

Neural Volterra filter for chaotic time series prediction

A new second-order neural Volterra filter （SONVF） with conjugate gradient （CG） algorithm is proposed to predict chaotic time series based on phase space delay-coordinate reconstruction of chaotic dynamics system in this paper, where the neuron activation functions are introduced to constraint Volterra series terms for improving the nonlinear approximation of second-order Volterra filter （SOVF）. The SONVF with CG algorithm improves the accuracy of prediction without increasing the computation complexity. Meanwhile, the difficulty of neuron number determination does not exist here. Experimental results show that the proposed filter can predict chaotic time series effectively, and one-step and multi-step prediction performances are obviously superior to those of SOVF, which demonstrate that the proposed SONVF is feasible and effective.     

用一种少参数非线性自适应滤波器自适应预测低维混沌时间序列

基于混沌动力系统的相空间延迟坐标重构,利用混沌序列固有的确定性和非线性,提出了用 于混沌时间序列预测的一种少参数非线性自适应滤波预测模型.该预测模型在Volterra自适 应滤波器的基础上引入sigmoid函数来减少待定参数.实验研究表明,这种少参数非线性自适 应滤波预测器仅需用50个样本经20次预训练后,就能有效地预测一些低维混沌序列,且这种 少参数非线性自适应滤波预测器更便于工程实现. 关键词： 混沌 非线性自适应预测 少参数非线性自适应滤波器 自适应算法     

Sparse modeling of super-resolution near-field structure read-out signals

In this study, super-RENS disc read-out signals were modeled with various nonlinear models. In the results of modeling the nonlinearity, DC offset, and domain bloom phenomena of the super-RENS channel with a second-order Volterra filter, it was identified that the number of significant quadratic coefficients was relatively small. Therefore, a sparse Volterra model and a truncated Volterra model are applied to effectively model the nonlinear channel. In addition, the Hammerstein-type asymmetric conversion model is employed to model the nonlinear channel for the purpose of comparison. The results demonstrate that the sparse model of a simplified polynomial form achieves good modeling performance for the super-RENS disc read-out signals.     

Three-dimensional spatiotemporal pulse characterization with an acousto-optic pulse shaper and a Hartmann-Shack wavefront sensor

We demonstrate a simplified arrangement for spatiotemporal ultrashort pulse characterization called Hartmann-Shack assisted, multidimensional, shaper-based technique for electric-field reconstruction. It employs an acousto-optic pulse shaper in combination with a second-order nonlinear crystal and a Hartmann-Shack wavefront sensor. The shaper is used as a tunable bandpass filter, and the wavefronts and intensities of quasimonochromatic spectral slices of the pulse are obtained using the Hartmann-Shack wavefront sensor. The wavefronts and intensities of the spectral slices are related to one another using shaper-assisted frequency-resolved optical gating measurements, performed at particular points in the beam. This enables a three-dimensional reconstruction of the amplitude and phase of the pulse. We present some example pulse measurements and discuss the operating parameters of the device.     

Long-distance fiber sensor system based on the second-order Raman pump and amplification

We demonstrate a novel technique to realize a long-distance fiber sensor system based on the second-order Raman pump and amplification. With the second-order Raman pump and amplification, a gain spectrum around 1582-nm is achieved. It serves as not only the optical source for the remote fiber sensor but also the filter to intensity modulated the wavelength shift of the fiber sensor. A long-distance fiber strain sensor system is demonstrated by adopting a fiber Fabry?CPérot sensor. Experimental results show that the wavelength shift of the sensor in response to the strain is simultaneously intensity modulated by the steep slope with a high sensitivity, while it is temperature insensitive. With the side gain spectrum served as a quasi-linear filter, the sensor can also be quasi-linearly intensity-modulated.     

Control of self-oscillation in systems with chaotic dynamics

A controllable self-oscillating system with self-switching that includes additional feedback in an oscillator consisting of a nonlinear amplifier, first-order and second-order filters, and a delay line configured into a closed loop is proposed. A mathematical model of the system and results of its numerical analysis are presented. It is shown that, in a system with time lag and a large inertia parameter, oscillation may become chaotic even if only regular oscillation takes place in the absence of self-switching. The effect of additional feedback on an oscillator-containing system without an inertia element, second-order filter, or delay line is considered.     

A genetic resampling particle filter for freeway traffic-state estimation

On-line estimation of the state of traffic based on data sampled by electronic detectors is important for intelligent traffic management and control.Because a nonlinear feature exists in the traffic state,and because particle filters have good characteristics when it comes to solving the nonlinear problem,a genetic resampling particle filter is proposed to estimate the state of freeway traffic.In this paper,a freeway section of the northern third ring road in the city of Beijing in China is considered as the experimental object.By analysing the traffic-state characteristics of the freeway,the traffic is modeled based on the second-order validated macroscopic traffic flow model.In order to solve the particle degeneration issue in the performance of the particle filter,a genetic mechanism is introduced into the resampling process.The realization of a genetic particle filter for freeway traffic-state estimation is discussed in detail,and the filter estimation performance is validated and evaluated by the achieved experimental data.     

RETRACTED: A Hybrid Nonlinear Active Noise Control Method Using Chebyshev Nonlinear Filter

Investigations into active noise control (ANC) technique have been conducted with the aim of effective control of the low-frequency noise. In practice, however, the performance of currently available ANC systems degrades due to the effects of nonlinearity in the primary and secondary paths, primary noise and louder speaker. This paper proposes a hybrid control structure of nonlinear ANC system to control the non-stationary noise produced by the rotating machinery on the nonlinear primary path. A fast version of ensemble empirical mode decomposition is used to decompose the non-stationary primary noise into intrinsic mode functions, which are expanded using the second-order Chebyshev nonlinear filter and then individually controlled. The convergence of the nonlinear ANC system is also discussed. Simulation results demonstrate that proposed method outperforms the FSLMS and VFXLMS algorithms with respect to noise reduction and convergence rate.     

Higher-order interference of low-coherence optical fiber sensors

The higher-order interference noise that is caused by multireflection at the fiber sensor's end surface in low-coherence fiber sensor array is proposed. The generation of the higher-order interference noise and its quantity and amplitude are theoretically analyzed. The second-order interference noises are experimentally demonstrated. The results show that the second-order noises arise in any sensor array composed of more than two sensors and the number of the second-order peaks is proportional to the third power of the sensor's number. The ratio of the amplitude of the second-order noise to that of the signal peak is proportional to the reflectivity of the sensor's end surface. In a sensor array, when the reflectivity is more than 10(-5), the amplitude of the second-order noise is higher than other noises and it becomes a main factor that determines the signal-to-noise ratio of the sensor arrays. Therefore, reducing the higher-order interference noise can improve the multiplexing capacity of the sensor array.     

Analysis of a second-order polarization-independent filter made of a single ring resonator and a Sagnac interferometer

A novel second-order polarization-independent filter made of a single ring resonator and a Sagnac interferometer (SRRSI) is proposed, and its filtering characteristics are investigated. By using birefringence in waveguide, a single ring resonator can be used to synthesize a filter with second-order response. Analytical formulas are derived for characteristics of the SRRSI varied with waveguide parameters, such as the coupling coefficient; and the critical condition of a second-order Butterworth filter is given. The influence of loss in the ring resonator is also analyzed.     

Optimal design of FIR beamformer with frequency invariant patterns

Two approaches to the optimal design of FIR beamformers with frequency invariant patterns using second-order cone programming (SOCP) are proposed. The first approach is a two-step method, which is implemented via separately optimal array pattern synthesis and optimal FIR filters design. The array weights for each frequency bin within the working frequency band are designed to insure that the array patterns approximate the reference ones. And the FIR filter corresponding to each sensor is designed to insure that the frequency responses approximate the array weights. The second approach is a direct method, in which the beam response is expressed as a linear function of FIR filter tap weights and the filters are designed by jointly optimizing the spatial and frequency responses to achieve the desired array patterns. All the optimal design problems (array pattern synthesis, FIR filter design and joint optimization) are formulated as the SOCP, which can be solved efficiently using the well-developed interior-point methods. Results of computer simulations and lake experiment for a twelve-element semicircular array confirm satisfactory performance of the two approaches proposed in this paper.     

逼近积分点数下限的五阶容积卡尔曼滤波定轨算法

为了在保持滤波定轨精度不变的条件下提高定轨计算的实时性,提出一种新的逼近积分点个数下限的五阶容积卡尔曼滤波定轨算法.首先,采用一种数值容积准则对非线性函数的高斯加权积分进行近似,该准则所需的积分点个数仅比五阶代数精度容积准则积分点个数的理论下限多一个积分点,并在贝叶斯滤波算法框架下推导出本文算法的更新步骤.然后,给出实时定轨所需的状态方程和量测方程,在状态方程中考虑了J2项引力摄动和大气阻力摄动,在量测方程中利用坐标系转换推导了轨道状态与测量元素之间的非线性关系.仿真实验结果表明,本文所提算法在定轨精度方面与已有的五阶滤波算法相当,但所需的积分点个数最少,计算实时性最高,从而验证了本文算法的有效性.     

基于二阶离散变分方法的非线性映射参数估计

提出一种估计非线性映射未知参数的二阶离散变分方法.首先针对非线性离散混沌系统, 利用变分方法导出了伴随方程和目标泛函梯度, 以此为基础利用二阶离散变分方法给出了二阶伴随方程和精确计算Hessian矩阵-向量乘积的显式表达式; 其次设计了估计非线性映射未知参数的新算法, 并以此对Hyperhenón映射和二维抛物映射中的未知参数进行了精确的估计. 数值仿真结果表明了该方法的有效性和优点. 关键词： 非线性映射 参数估计 二阶离散变分方法 伴随方程     

A shock-capturing methodology based on adaptative spatial filtering for high-order non-linear computations

A shock-capturing methodology is developed for non-linear computations using low-dissipation schemes and centered finite differences. It consists in applying an adaptative second-order filtering to handle discontinuities in combination with a background selective filtering to remove grid-to-grid oscillations. The shock-capturing filtering is written in its conservative form, and its magnitude is determined dynamically from the flow solutions. A shock-detection procedure based on a Jameson-like shock sensor is derived so as to apply the shock-capturing filtering only around shocks. A second-order filter with reduced errors in the Fourier space with respect to the standard second-order filter is also designed. Linear and non-linear 1D and 2D problems are solved to show that the methodology is capable of capturing shocks without providing dissipation outside shocks. The shock detection allows in particular to distinguish shocks from linear waves, and from vortices when it is performed from dilatation rather than from pressure. Finally the methodology is simple to implement and reasonable in terms of computational cost.     

A Widely Tunable Photonic-Assisted Microwave Notch Filter with High Linearity Using a Dual-Parallel Mach-Zehnder Modulator

A widely tunable microwave photonic(MWP) notch filter with high linearity based on a dual-parallel MachZehnder modulator(DPMZM) is proposed and experimentally demonstrated.The motivation of this work lies in the fact that the MWP notch filter previously reported has nonlinear distortions generally induced by the nonlinear property of electro-optic devices.In this scheme,even-order modulated sidebands at the DPMZM output are effectively suppressed by properly adjusting bias voltages of the DPMZM,which are the dominant factor to induce the nonlinear distortions into the MWP notch filter.The proposed scheme is theoretically analyzed and experimentally verified.     

A monotone finite volume method for advection–diffusion equations on unstructured polygonal meshes

We present a new second-order accurate monotone finite volume (FV) method for the steady-state advection–diffusion equation. The method uses a nonlinear approximation for both diffusive and advective fluxes and guarantees solution non-negativity. The interpolation-free approximation of the diffusive flux uses the nonlinear two-point stencil proposed in Lipnikov [23]. Approximation of the advective flux is based on the second-order upwind method with a specially designed minimal nonlinear correction. The second-order convergence rate and monotonicity are verified with numerical experiments.     

Sampling strong tracking nonlinear unscented Kalman filter and its application in eye tracking

The unscented Kalman filter is a developed well-known method for nonlinear motion estimation and tracking. However, the standard unscented Kalman filter has the inherent drawbacks, such as numerical instability and much more time spent on calculation in practical applications. In this paper, we present a novel sampling strong tracking nonlinear unscented Kalman filter, aiming to overcome the difficulty in nonlinear eye tracking. In the above proposed filter, the simplified unscented transform sampling strategy with n+2 sigma points leads to the computational efficiency, and suboptimal fading factor of strong tracking filtering is introduced to improve robustness and accuracy of eye tracking. Compared with the related unscented Kalman filter for eye tracking, the proposed filter has potential advantages in robustness, convergence speed, and tracking accuracy. The final experimental results show the validity of our method for eye tracking under realistic conditions.     

Multiwavelength fiber laser with fine adjustment, based on nonlinear polarization rotation and birefringence fiber filter

We have proposed and demonstrated a multiwavelength fiber laser based on nonlinear polarization rotation (NPR). The mechanism for stable room-temperature multiwavelength operation contributes to the ability of the intensity-dependent loss in NPR to effectively alleviate mode competition. In addition, through tuning the birefringence fiber filter, the lasing wavelength can be accurately tuned in the free spectrum range of the in-line periodic filter.