All-optical NRZ-OOK-to-RZ-OOK format conversions with tunable duty cycles using nonlinear polarization rotation of a semiconductor optical amplifier

We experimentally demonstrate an all-optical 10 Gb/s format conversion from non-return-to-zero (NRZ) on-off-keying (OOK) to return-to-zero (RZ)-OOK with tunable duty cycle in the whole C-band using nonlinear polarization rotation (NPR) arising in an semiconductor optical amplifier (SOA). The experimental results show that, by tuning the polarizer at the SOA output, an RZ signal with tunable duty cycle from 33% to 66% could be obtained with an extinction ratio(ER) over 10 dB. In addition, we show that the NRZ-to-RZ conversion with duty cycle of 33-66% can be obtained with less than 1 dB power penalty at the bit error ratio (BER) of 10⁻⁹. The device can facilitate the cross-connection between optical transmission networks employing different modulation formats.     

光锥与CCD耦合器件调制传递函数的测试方法

采用直接对倾斜刀口成像的方法测量光锥与CCD耦合器件的调制传递函数.这种方法对静止刀口成像,利用刀口与光锥纤维列间的一定倾斜角度,在垂直于刀口的不同行之间形成不同的值,代替了传统刀口扫描中的扫描装置,并无需保证刀口与阵列的平行,相应地减小了测量误差. 在数据处理中采用了二次平均法,即对同一幅图像得出的不同位置值进行平均及多次测量结果平均,在一定程度上消除了由于离散性产生的空间非平移不变性的影响.     

超高速行波电吸收调制器的k值设计方法

介绍了一种用于超高速行波电吸收调制器(TW-EAM)设计的“k值带宽法”.该方法考虑了影响调制器带宽的阻抗失配、相速度失配、微波衰减等因素,说明一个优化设计的TW-EAM其带宽可达到140 GHz.     

Remarks on Fourier multipliers and applications to the wave equation

Exploiting continuity properties of Fourier multipliers on modulation spaces and Wiener amalgam spaces, we study the Cauchy problem for the NLW equation. Local wellposedness for rough data in modulation spaces and Wiener amalgam spaces is shown. The results formulated in the framework of modulation spaces refine those in [A. Bényi, K.A. Okoudjou, Local well-posedness of nonlinear dispersive equations on modulation spaces, preprint, April 2007 (available at ArXiv:0704.0833v1)]. The same arguments may apply to obtain local wellposedness for the NLKG equation.     

Band structure investigations of GaN films using modulation spectroscopy

The paper presents investigation results concerning band structure of gallium nitride and position of intrinsic and associate defect levels. Main optical characteristics (transmission, reflection and luminescence) were measured in both ordinary and λ-modulation mode for epitaxy-grown GaN films, allowing to determine valence band splitting caused by spin-orbital interaction (48 meV) and crystalline field (10 meV). Analysis of photoluminescence spectra made it possible to identify main recombination mechanisms involving donor and acceptor levels formed by intrinsic point defects , and their associates.     

油页岩含油率近红外光谱原位分析方法研究

为实现油页岩含油率的原位检测,采用便携式近红外光谱分析技术,针对吉林扶余油页岩基地2号钻井的66个岩芯样品开展了原位检测的分析建模方法研究。采用自制便携式近红外光谱仪器获得反射率、吸光度、K-M函数三种数据形式光谱数据,结合主成分-马氏距离(PCA-MD)剔除异常样品、无信息变量消除法(UVE)波长筛选及二者组合的四种建模数据优化方法,采用相同的数据预处理方法进行偏最小二乘(PLS)和反向传播神经网络(BPANN)两种方法的建模分析研究,确定最佳分析模型及方法。结果表明(1)不论是否采用四种不同的数据优化方法,两种建模方法所用建模数据库适合采用反射率或K-M函数的光谱数据形式;(2)两种建模方法,采用四种不同的数据优化方法,对相同数据库建模精度的影响不同：采用PLS建模方法、以PCA-MD和UVE+ PCA-MD两种方法进行数据优化、可以提高K-M函数光谱数据形式数据库的建模分析精度,采用BPANN建模方法、以UVE、PCA-MD 与UVE组合的 三种方法进行数据优化、对三种数据形式数据库的建模精度均有所提高;(3)除以反射率光谱数据并进行PCA-MD数据优化外,采用BPANN方法的建模精度好于PLS法。其中采用反射率光谱数据形式、只进行UVE数据优化外的BPANN建模精度最高,预测相关系数为0.92、标准偏差为0.69%。     

Learning to short-time Fourier transform in spectrum sensing

The future wireless communication will come up with a strict requirement on high spectral efficiency, developing novel algorithms for spectrum sensing with deep sensing capability will be more challenging. However, traditional expert feature-based spectrum sensing algorithms are lack of sufficient capability of self-learning and adaptability to unknown environments and complex cognitive tasks. To address this problem, we propose to build up a deep learning network to learn short time-frequency transformation (STFT), a basic entity of traditional spectrum sensing algorithms. Spectrum sensing based on the learning to STFT network is supposed to automatically extract features for communication signals and makes decisions for complex cognitive tasks meanwhile. The feasibility and performances of the designed learning network are verified by classifying signal modulation types in deep spectrum sensing applications.