Noise helped manifestation of intrinsic frequency: A case study in the mesoscopic hormone signaling system

The selective sustainment of nonlinear systems to signals is of great significance to signal transduction in living systems. We take hormone signaling as an example, and investigate the sustainment of internal and external signals. Simulation results prove that signals with "intrinsic frequency", no matter if it is noise induced or external injected, can be selectively sustained by exploiting internal and/or external noise. Both the internal and external noise can optimize the noise-induced signals, and the optimization is rather robust to the disturbance of external signals with other frequencies. These results are of significance for weak signal detection and trausduction in the presence of external signals.     

一个求解旅行商问题的松弛算法

在旅行商问题（TSP）的传统模型中，子回路消除约束的数量随着问题规模的增大具有指数增长的特性，极大地限制了TSP的求解效率。基于TSP的松弛问题，本文提出一种有效生成子回路消除约束的方法。该方法通过求解一系列线性整数规划，来实现TSP的精确快速求解。数值结果表明，本方法相比于采用Cplex直接求解，能够更快地找到TSP的最优解。     

基于时变相量的配电网PT铁磁谐振研究与措施分析

利用相模变换理论,建立了配电网发生绝缘放电时的故障分析模型,分析了配电网PT发生铁磁谐振的原因及稳态谐振的发生机理.根据系统的0模网络的ΔI(φL)曲线提出了加装零序PT抑制铁磁谐振的方法,以避免系统发生工频铁磁谐振.     

环糊精对莲藕汁饮料的除涩味作用探讨

本文研究了环糊精复合莲藕汁饮品中涩味物质—鞣质的最佳条件:以质量比为3:7的α、β复合环糊精为除涩剂;用量为2.5g/L;pH值为8.0;温度为70℃;搅拌速度为1000r/min;反应时间为3h.结果表明:环糊精包覆后明显提高了莲藕汁饮料的品质,去除了涩味,并提高了稳定性.     

中学校园网络故障与排除浅析

校园网络在维护过程中,故障极为频繁,故障种类十分繁杂,怎样尽可能地减少校园网故障,以及故障发生后能及时解决,是每一个维护人员都希望做到的。通过网络管理工作所积累的一些经验,以期抛砖引玉,共同掌握校园网故障与排除的方法,提高校园网维护效率。     

一种奇异混合信号盲分算法的稳定性分析

混合信号盲分问题是一类很难而又具有很强应用背景的问题,以往对这类问题的研究均在混合矩阵为非奇异的条件下进行。给出一种神经网络模型及相应算法,处理混合矩阵为奇异的混合信号盲分问题,并分析了算法的稳定性。     

浅析外界电磁场对有线通信设备的干扰

随着科技的发展,远洋船上处处运用高科技,且使用大量的电子设备。电子设备运行时产生的电磁能量,干扰有线通信设备十分常见,给船员的工作和生活带来较大影响。本文立足工作实际,就电话机受干扰情况进行了详细分析,论述了产生噪声的原因。同时本文对分析船指挥调度设备噪音产生的原因也有一定的借鉴作用。     

轮胎空腔共振噪声的改进方法

汽车在行驶中，轮胎内部空腔共振将引起车辆的内部噪声. 首先论述轮胎内 部空腔共振噪声的特性, 然后推导声腔系统的运动方程, 进而提出一种降低轮胎声腔共振固有频率峰值的改进方法, 最后用实验验证其方法的正确性。     

New approach to eliminate structural redundancy in case resource pools using α mutual information

Structural redundancy elimination in case resource pools (CRP) is critical for avoiding performance bottlenecks and maintaining robust decision capabilities in cloud computing services. For these purposes, this paper proposes a novel approach to ensure redundancy elimination of a reasoning system in CRP. By using α entropy and mutual information, functional measures to eliminate redundancy of a system are developed with respect to a set of outputs. These measures help to distinguish both the optimal feature and the relations among the nodes in reasoning networks from the redundant ones with the elimination criterion. Based on the optimal feature and its harmonic weight, a model for knowledge reasoning in CRP (CRPKR) is built to complete the task of query matching, and the missing values are estimated with Bayesian networks. Moreover, the robustness of decisions is verified through parameter analyses. This approach is validated by the simulation with benchmark data sets using cloud SQL. Compared with several state-of-the-art techniques, the results show that the proposed approach has a good performance and boosts the robustness of decisions.     

Hyperion高光谱数据条带噪声消除方法研究

高光谱图像条带噪声的消除是高光谱图像处理的关键预处理技术.概述Hyperion成像光谱仪的工作原理,分析了Hyperion数据条带噪声产生的机理并总结条带噪声的特性.提出高光谱条带噪声消除的4种方法.研究表明,Hyperion数据条带噪声消除比较有效的方法是矩匹配法.对于高光谱图像条带噪声消除深层次的研究是要实现高光谱图像条带噪声的自动检测以及处理的智能化.