Variational Solution of Stochastic Schrödinger Equations With Power-Type Nonlinearity

We investigate a Schrödinger problem with multiplicative Gaussian noise term and power-type nonlinearity on a bounded one-dimensional domain. In order to prove the existence and uniqueness of the variational solution, a further process will be introduced which allows to transform the stochastic nonlinear Schrödinger problem into a pathwise one. Galerkin approximations and compact embedding results are used.     

光学频率梳非线性传输及其在相位噪声探测中的应用

光纤传递链路中相位噪声探测是基于光纤的精确射频标准传递系统中重要组成部分。为解决光纤链路相位噪声探测中节点反射干扰的问题, 本文基于广义非线性薛定谔方程, 理论上研究了窄带光学频率梳在色散位移光纤中的非线性光学传播特性。在理论分析的基础上, 结合密集波分复用架构, 提出了一种基于锁模光学频率梳进行光纤传递射频信号的相位噪声探测新技术, 克服了节点反射干扰, 给出了初步实验验证。     

Toward automatic evaluation of defect detectability in infrared images of composites and honeycomb structures

Non-destructive testing (NDT) refers to inspection methods employed to assess a material specimen without impairing its future usefulness. An important type of these methods is infrared (IR) for NDT (IRNDT), which employs the heat emitted by bodies/objects to rapidly and noninvasively inspect wide surfaces and to find specific defects such as delaminations, cracks, voids, and discontinuities in materials. Current advancements in sensor technology for IRNDT generate great amounts of image sequences. These data require further processing to determine the integrity of objects. Processing techniques for IRNDT data implicitly looks for defect visibility enhancement. Commonly, IRNDT community employs signal to noise ratio (SNR) to measure defect visibility. Nonetheless, current applications of SNR are local, thereby overseeing spatial information, and depend on a-priori knowledge of defect’s location. In this paper, we present a general framework to assess defect detectability based on SNR maps derived from processed IR images. The joint use of image segmentation procedures along with algorithms for filling regions of interest (ROI) estimates a reference background to compute SNR maps. Our main contributions are: (i) a method to compute SNR maps that takes into account spatial variation and are independent of a-priori knowledge of defect location in the sample, (ii) spatial background analysis in processed images, and (iii) semi-automatic calculation of segmentation algorithm parameters. We test our approach in carbon fiber and honeycomb samples with complex geometries and defects with different sizes and depths.     

How Many Molecules are Required to Obtain a Steady Faradaic Current from Mediated Electron Transfer at a Single Nanoparticle on a Supporting Surface?

We investigate the chronoamperometric noise characteristics of electron‐transfer reactions occurring on single nanoparticles (NPs) and assemblies of well‐separated NPs on a supporting surface. To this end, we combine a formerly described expression for the steady‐state current of a single particle with the shot‐noise model and derive an expression for the signal‐to‐noise ratio as a function of bulk concentration and particle radius. Our findings are supported by random‐walk simulations, which closely match the analytical results.     

Wavelet transforms in separation science for denoising and peak overlap detection

Wavelet transform is a versatile time‐frequency analysis technique, which allows localization of useful signals in time or space and separates them from noise. The detector output from any analytical instrument is mathematically equivalent to a digital image. Signals obtained in chemical separations that vary in time (e.g., high‐performance liquid chromatography) or space (e.g., planar chromatography) are amenable to wavelet analysis. This article gives an overview of wavelet analysis, and graphically explains all the relevant concepts. Continuous wavelet transform and discrete wavelet transform concepts are pictorially explained along with their chromatographic applications. An example is shown for qualitative peak overlap detection in a noisy chromatogram using continuous wavelet transform. The concept of signal decomposition, denoising, and then signal reconstruction is graphically discussed for discrete wavelet transform. All the digital filters in chromatographic instruments used today potentially broaden and distort narrow peaks. Finally, a low signal‐to‐noise ratio chromatogram is denoised using the procedure. Significant gains (>tenfold) in signal‐to‐noise ratio are shown with wavelet analysis. Peaks that were not initially visible were recovered with good accuracy. Since discrete wavelet transform denoising analysis applies to any detector used in separation science, researchers should strongly consider using wavelets for their research.     

开式轴流风扇气动噪声预测

本文采用LES/FW-H的匹配方法,研究了开式轴流风扇内部旋涡流动特征及其与叶片表面干涉引起的气动噪声之间的联系,同时进行了远场噪声预测,探讨了叶轮不同表面辐射噪声时的频谱分布特征.研究结果表明,开式轴流风扇吸力面附近形成的叶尖涡和前缘分离涡在吸力面叶片表面相应位置形成大压力波动,形成主要噪声源;叶片吸力面的辐射噪声可以通过改善吸力面附近的旋涡流动来降低;低速轴流叶轮由叶轮壁面辐射的噪声以宽频成分为主.     

基于半导体光放大器的干涉型器件中噪声特性的分析

分析了基于半导体光放大器(SOA)的干涉仪分别处于“开”、“关”两种工作状态时的输出信噪比及噪声指数,发现当干涉仪处于“开”态时输出信噪比有所恶化,并导出了附加噪声因子的表达式。实验结果进一步证明了理论分析的正确性。     

天文观测相机低噪声CCD视频处理电路的分析与设计

在讨论天文观测相机低噪声视频处理电路的基础上,对前置放大、差分放大、可编程增益放大、相关双采样及16bit模数转换等关键组成部分进行了分析,给出各组成部分的设计方法。对所设计的低噪声视频处理电路进行了PSPICE仿真和实验测试,仿真和实验结果表明,该视频处理电路在本身引入噪声较小的同时,有效地抑制了CCD的复位噪声和1/f等低频噪声,使天文观测相机的整机噪声<15e-,达到了指标要求。     

大孔径静态干涉成像光谱仪的信噪比分析

根据大孔径静态干涉成像光谱仪的原理和特点,分析了光辐射能在光学系统内的传输情况,对探测器上接收到的光辐射能信号和噪音信号做了详细的推导,得到了仪器理论信噪比的表达式.在实验上以大口径积分球为辐射源,采集仪器输出的干涉图像,计算得到仪器的实际信噪比曲线,对大孔径静态干涉成像光谱仪的理论信噪比曲线与实际的信噪比曲线做分析比较,结果验证了用推导的论信噪比的表达式来预估仪器信噪比的可行性.