Accurate measurement of capture cross sections in deep level transient spectroscopy: Application to EL2 in GaAs

A rigorous formulation of capacitance changes during trap filling processes is presented and used to accurately determine the electron capture cross section of EL2 in GaAs at a particular temperature, 377K, in this case. The value, σ_n (377K) = 2.7 × 10⁻¹⁶ cm², is compared with that predicted from the emission dependence.     

数字微波无线通信系统中的中频自适应均衡器

在数字微波无线通信系统中，由于多径衰落引起码间干扰，使系统性能恶化，必须采用抗多径衰落的措施．中频频域均衡器（ＩＦＥ）由于结构简单而且经济，在衰落不十分严重的情况下性能良好，因而在数字微波系统中被广泛采用．本文比较了几种常用的ＩＦＥ，并着重对自适应谐振武中频均衡器的两种调节方法作了研究．模拟计算得到的ｓｉｇｎａｔｕｒｅ曲线表明，这种均衡器对非最小相位（ＭＭＰ）信道的传输性能有很大的改进，且两种调节法可达到相近的结果，如选择其中较简单的调节法，可以简化硬件结构．     

TPLIB－94 69群截面库的研制

介绍了ＴＰＬＩＢ－９４６９群截面库的研制。此载面库可供ＴＰＦＡＰ和ＣＡＲＭＰ等热中子反应堆物理计算程序使用。     

10MeV中子引起的~（238）U，~（209）Bi，Fe和~9Be的次级中子

１０ＭｅＶ中子引起的￣（２３８）Ｕ，￣（２０９）Ｂｉ，Ｆｅ和￣９Ｂｅ的次级中子双微分截面测量祁步嘉，唐洪庆，周祖英，周陈维，沈冠仁，柯尊建，孙振强，夏海鸿（中国原子能科学研究院核物理所，北京２７５－４６信箱，１０２４１３）次级中子双微分截面是核工程设...     

通信接收机的抗信道干扰问题

接收机产生干扰的机理分析是提高其抗干扰性能的基础和前提,为此文中对其作了详细阐述,并对降低接收机共信道干扰的改善措施也作了简明分析研究。本文为从事通信工作者理解与应用有关内容提供一轮廓性依据。     

Identification of delayed system using instrumental variable method

System identification uses system inputs and outputs to raise mathematical models.Various techniques of system identification exist that offer a nominal model and an uncertainty bound.Many practical systems such as thermal processes & chemical processes have inbuilt time delay.If the time delay used in the system model for controller design does not concur with the actual process time delay,a closed-loop system may be unstable or demonstrate unacceptable transient response characteristics so here the time delay is assumed to be time-invariant. This paper proposes on-line identification of delayed complex/uncertain systems using instrumental variable(Ⅳ) method.Parametric uncertainty has been considered which may be represented by variations of certain system parameters over some possible range.This method allows consistent estimation when the system parameters are associated with the noise terms,as the IV methods(IVM’s)usually make no assumption on the noise correlation configuration.The faster convergence of the parameters including noise terms has been proved in this paper.Iterative prefiltering(IP)method has also been used for the identification of the delayed uncertain system and the graphical results given in this paper demonstrate that the convergence results are inferior to the instrumental variable method.     

给排水设备的电气控制安装与调试

针对2011年和2012年全国中职院校竞赛项目使用的《建筑设备给排水控制调试装置》设备,对其电气控制部分的安装调试过程进行分解。     

多分量调频信号的阵列处理时频交叉项的抑制方法

在应用时频-MUSIC方法对多分量调频信号进行到达角估计的问题中,针对时频分布中交叉项的存在对估计性能的影响,提出了一种基于阵列信号处理抑制时频分布交叉项的新方法。该方法利用多信源在各阵元上的延迟对时频分布交叉项振荡相位的影响,联合运用多通道信号处理和图像处理的方法,采用二维乘法滤波,减小高频振荡交叉项在时频图像中的占据区域,从而达到抑制交叉项的目的。仿真实验显示该方法具有良好的效果。     

Concurrent reading while writing revisited

A modification is proposed to Peterson's construction of 1-writern-reader multivalued atomic shared variableusingn+2 multivalued safe variables and some boolean atomic variables. The resulting construction is elegant and is simpler than the original one. K. Vidyasankar received B.E. (Elec. Engg.) from Thiagarajar College of Engineering, Madurai, M. Tech. from I.I.T. Kanpur, India, and Ph.D. in Computer Science from University of Waterloo, Canada. He is now an Associate Professor in Computer Science at Memorial University of Newfoundland, Canada. His research interests include concurrency control and recovery in database systems, concurrency in interprocess communication, design and analysis of algorithms, and graph theory.A prelininary version of this paper, under the title Improving Peterson's Construction of 1-Writern-Reader Multivalued Atomic Register, appears in the Proc. 26th Annual Allerton Conference on Communication, Control, and Computing, University of Illinois at Urbana Champaign, September 1988, pp 693–700     

Cross lingual speech emotion recognition via triple attentive asymmetric convolutional neural network

The application of cross‐corpus for speech emotion recognition (SER) via domain adaptation methods have gain high acknowledgment for developing good robust emotion recognition systems using different corpora or datasets. However, the issue of cross‐lingual still remains a challenge in SER and needs more attention to resolve the scenario of applying different language types in both training and testing. In this paper, we propose a triple attentive asymmetric convolutional neural network to address the recognition of emotions for cross‐lingual and cross‐corpus speech in an unsupervised approach. The proposed method adopts the joint supervision of softmax loss and center loss to learn high power discriminative feature representations for target domain via the use of high quality pseudo‐labels. The proposed model uses three attentive convolutional neural networks asymmetrically, where two of the networks are used to artificially label unlabeled target samples as a result of their predictions from training on source labeled samples and the other network is used to obtain salient target discriminative features from the pseudo‐labeled target samples. We evaluate our proposed method on three different language types (i.e., English, German, and Italian) data sets. The experimental results indicate that, our proposed method achieves higher prediction accuracy over other state‐of‐the‐art methods.