查询词典 neural network

The proportion of rents that firms get depends on their network capability. This reveals the essential relationships between network resource, network rents and network capability: First of all, network rents come from the network resources. Furthermore, network rent is the representative of the competitive advantage and the value of the network resource. Second, network resource is the foundation of the network capability, the function of network capability is activated in the process of using network resource by firm. It enables the network resource to be a potential value resource of the competitive advantage. At last, network capability activates the network rents in the network resource, and make sure that the firm get the additional benefit;(4) the network capability can be classified as: network visioning capability, network constructing capability, network operating capability and network constructing capability. Some factors, such as maturity of IT, openness of culture, management system involved, experience of participation in network, have a positive effect on the network capability of the firm;(5) the impact of network capability on innovation performance is realized through knowledge transfer between network partners, namely, knowledge transfer is the mediator; and (6) the type of innovation network, exporation network or exploitation network, has moderator effect on the relationship of network capability and knowledge transfer, and network capability and innovation performance as well. In the exploration network, network constructing capability has more effect on the performance of the knowledge transfer and innovation. In the exploitation network, network operating capability has more effect on the performance of the knowledge transfer and innovation.

通过对创新网络环境下网络资源、网络租金和网络能力的概念界定和内涵分析，本研究辨析了三者之间以及它们与竞争优势之间的本质关系：首先，网络资源是网络租金的来源，而网络租金是企业竞争优势的表征，也是网络资源的价值体现；其次，网络资源是网络能力的基础，而网络能力在运用网络资源的过程中发挥其作用，实现了网络资源成为竞争优势源泉的内在价值；最后，网络能力激活了蕴涵在网络资源中的网络租金，并确定企业获得这种额外收益的份额，网络租金正是网络能力发挥作用的成果；(4)企业网络能力可以分成网络规划能力、网络配置能力、网络运作能力和网络占位能力四种，本研究的实证结果表明企业的IT成熟度、文化开放度、网络管理体系和网络活动经验都能够正向影响企业的网络能力水平，因而企业可以通过改善上述各种因素的水平来实现提升企业网络能力的水平；(5)企业网络能力对企业创新绩效的促进作用更多地是通过正向影响知识转移实现的，即知识转移在其中起到了中介作用；(6)创新网络的类型，即探索型创新网络和利用型创新网络，分别在网络配置能力和网络运作能力与知识转移之间的关系中，以及在网络配置能力和网络运作能力与创新绩效之间的关系中起到调节作用，在探索性创新网络中，企业的网络配置能力对提升企业获得的知识转移绩效和创新绩效更为重要；而在利用性创新网络中，企业的网络运作能力对提升企业获得的知识转移绩效和创新绩效更为重要。

In such doing, this dissertation serves as a step stone for papers of its counterparts to come, and, more importantly, it proposes a strategic alternative to the realization of models for image processing. This dissertation consists of three major parts. In the first part, detailed discussions and delicate analyses of academic papers on Cellular Neural Network will be provided in the hope of helping us see the potentiality of Cellular Neural Network in the applications of image processing. I will focus on the aforementioned limitations on hardware compilation as well. In the second part, I will put forth "texture analysis" as one basic model of analysis when we apply Cellular Neural Network to image processing. In this so-called texture analysis, a useful "spatial feature" is especially drawn to help us overcome possible problems of more complicated Cellular Neural Network applications in image processing."Spatial feature" also serves as a well-functioning mechanism for technology of image identification. In the last part of this thesis, I will look into a case study, where Cellular Neural Network is applied to help de-screen document image. Using it as an example, we will see how algorithms of Cellular Neural Network may be of marvelous use in applications in document image processing, since it would reduce a great deal of calculation and computation when applied to software compilation, yet opens up unlimited possibilities for higher-speed hardware compilation of high-level image processing.

这篇论文主要可以分为三大部分：在第一部份里，我们会详细地说明并讨论在过去到现在大部分将分子类神经网路应用於影像处理的相关文献及未来所有可能的发展和技术，另外也将分子类神经网路作一完整的介绍，除此之外，我们也会特别著重於分子类神经网路在影像处理相关应用理论的讨论以及其硬体实现化的考量；在第二部分里，我们提出了一个将分子类神经网路应用於影像辨识处理的基础分析—纹路分析，这是由於纹路分析的复杂性和普遍性会使得分子类神经网路於高阶影像处理的应用不会只局限在单一的影像处理技术，其中我们也提出了一个相当有用的空间特徵，此一特徵不但可以使复杂地高阶影像处理能够应用分子类神经网路，也为影像辨识技术提供了一个很好的辨识机制；在最后一部分里，我们也将文件影像分析做了一个完整的剖析，并以文件影像的去网点为例来说明在实际情况下的分子类神经网路的应用，如此演算法的开发也为文件影像处理提供了更多实际的应用，更考量了文件影像处理若以软体实现时的计算量负荷，而对未来高阶数位影像处理能够以硬体实现来提高处理速度提供了无限的可能。

objective the aim of this study is to investigate the expression and the distribution of the nerve growth factor during the period of neural tube development of human embryo.method early development of neural tube was studied in human embryos about 35 gestational days by using immunocytochemical abc technique.result there were ngf immuno-positive substances in the cytoplasm and nuclei of neuroepithelial cells in the ventricular zones of neural tube.in the intermediate zone of neural tube,ngf immunoreactivity was detected in the nuclei of some neurons,or the processes of other neurons which contained no ngf-immunoreactive substances in their nuclei;the expression pattern of ngf in the marginal zone of neural tube was similar to that of the intermediate zone.the density of ngf-immunorecative particles was higher on the rostrum side of neural tube than on the caudal side.the ngf immuno-positive cells were also observed among the somites of embryo under the neural tube.conclusion these results suggest that ngf was an important signal molecule to induce neural tube differentiation,and that ngf may play a significant role in regulation of the biological function of neurons in developing neural tube.

目的 研究捷安肽素的抗真菌作用机理。方法采用形态学方法和同位素标记法。显微形态观察经捷安肽素处理后的供试真菌的形态学变化。进一步采用14c同位素标记的特异底物&尿苷二磷酸-（14c）-葡萄糖&示踪，研究捷安肽素对真菌(1，3)-β-d-葡聚糖合成酶活性反应的影响。结果研究神经生长因子在早期人胚神经管发育过程中的定位表达。方法采用免疫细胞化学 abc法染色，研究35天人胚的发育情况。结果在人胚神经管的室管带中，神经元的细胞质和细胞核ngf免疫反应阳性；在中间带，一部分神经元的细胞核ngf免疫反应阳性，另外一部分神经元的细胞核ngf免疫反应阴性，而其突起ngf免疫反应阳性；在边缘带ngf的表达与中间带相似。在神经管的头侧ngf阳性反应较强，神经管的尾侧ngf阳性反应较弱。结论 ngf在人胚神经管免疫反应阳性，表明ngf可能是诱导神经管分化发育的重要信号分子，提示ngf可能在人胚神经管的发育中具有十分重要的作用。神经生长因子；人胚；神经管；发育

The uniform approximation of normal wavelet neural network and the robust analysis of wavelet neural networks of the combination of Sigmoid function are detailedly introduction; Multiple model failure detection based on wavelet neural network is demonstrated detailedly; At last, the failure diagnosis results of aerocraft is present seperately by employing wavelet neural network and BP neural network, and the fault diagnosis of areocraft system by wavelet neural network is achieved.

论文以小波神经网络为研究对象，提出了一类新的加权小波基，分析证明了加权小波基的诸多良好特性；对于常见小波神经网络的一致逼近特性、S型函数组合小波神经网络的鲁棒性分析、多模型小波神经网络的故障检测等问题给出了详细的论证；最后，针对歼击机的常见故障问题，分别给出了应用小波神经网络和BP神经网络的故障诊断结果，实现了小波神经网络对飞机系统的故障诊断。

In this paper, the theory of artificial neural network is summarized; the analyse on BP neural network model is put stress on. For the predominance of artificial neural network"s dealing with non-linear complicated relation, the technology of artificial neural network is introduced into the evaluation of the highway bridge"s carrying capacity; and the preferences , the collection and disposal of stylebook, the structuring of BP neural network model are analyzed.

文中对人工神经元网络理论进行了综述，重点对神经元网络的BP算法进行了分析，利用人工神经元网络处理非线性复杂关系的优势，将人工神经元网络技术引入到公路桥梁承载力评估中；并对其中的参数选择、样本收集与处理、构造BP网络模型等进行了分析。

In this paper, the concept of network security and security structures of OSI and Internet is introduced, and various threats confronting the computer network are also discussed. Several kinds of network information security technologies, including firewall technology, virtual private network, intrusion detection system, data encryption technology, identity authentication and security protocol etc. are also examined. The security of internal network is the biggest problem in the construction of each network. The solution to this problem lies in setting up a firewall. The theory of a firewall and the approach to its actualization is studied. Intrusion detection system, an important part of the computer network security system, has gained extensive attention. IDS monitors the computer and network traffic for intrusion and suspicious activities. It not only detects the intrusion from the extranet hacker, but also the intranet users. The emergence of virtual private network paves the way for realizing secure connection of LAN quickly and at a relatively low cost. The concept, function, key techniques, including the tunnel technology, and the ways to realize VPN are expounded in this paper. Also introduced is the data encrypt network technology, which is called the soul of computer network security, such as digital digest, digital signature, digital certificate, digital encrypt arithmetic and so on. At the same time, the principle and the process of implementing network security by digital certificate and digital signature, the basic principle and characters of security protocols, and finally, three of the security protocols, concerning the security problems in network, IPsec, SLL and SET are analyzed in detail Computer network system should be a system of dynamic defence, both dynamic and static, passive as well as active, and even offensive, combined with management and technology.

本文系统地介绍了网络安全的概念、OSI及Internet的安全体系结构，并讨论了计算机网络面临的各种安全威胁；内部网络的安全问题是每个建网单位面临的最大问题，可以认为防火墙技术是解决网络安全的一个主要手段，本文研究了防火墙的原理及其实现手段；作为一种主动的防御措施，入侵检测系统作为网络系统安全的重要组成部分，得到了广泛的重视，TDS对计算机和网络资源上的恶意使用行为进行识别和响应，不仅检测来自外部的入侵行为，也监督内部用户的未授权活动；虚拟专用网技术的出现，为实现网络间的连接提供了快速安全但又相对便宜的手段，本文较深入的探讨了实现VPN的隧道技术，并对VPN的概念、功能、实现途径、基本构成、关键技术及发展前景等问题进行了全面论述；数据加密技术是网络安全核心技术之一，本文从数据加密算法、数字摘要、数字签名及数字证书等几方面简要介绍了数据加密技术，并分析用数字证书和数字签名实现网络安全的原理和过程；对安全协议的基本原理、主要特点进行了较为深入的研究，并就网络的安全性问题剖析了三种安全协议：IPsec协议、SLL协议和SET协议。

First, the traffic flow time series chaotic feature is extracted by chaos theory. pretreatment for traffic flow time series, and the wavelet neural networks model was build by this. Second, the chaotic mechanism and the chaotic probability is described. Based on chaotic learning algorithm, and the wavelet neural networks fast learning algorithm of traffic flow time series is designed based on chaotic algorithm. Last, a single-step and multi-step prediction of traffic flow chaotic time series is researched by BP neural networks, wavelet neural networks and wavelet neural networks based on chaotic algorithm. The results showed that the wavelet neural networks predictive performance is better than the BP networks and the wavelet neural networks by the simulation results and root-mean-square value.

首先，通过混沌理论提取了交通流量时间序列的混沌特征，并在此基础上建立了小波神经网络交通流量时间序列模型；接着，阐述了混沌学习算法的混沌机理、混沌产生的概率，设计了基于混沌算法的小波神经网络交通流量混沌时间序列快速学习算法；最后利用交通流量混沌时间序列对BP网络、非混沌算法的小波神经网络以及基于混沌算法的小波神经网络进行了单步预测和多步预测，并对预测结果的仿真图和真实值与预测值的方均根进行了比较，结果表明基于混沌学习算法的小波神经网络的预测性能明显优于应用BP网络和非混沌算法的小波神经网络。

Aiming at the disadvantage of conventional BP neural network, such as selecting parameter values by the empirical method, slow convergence speed and easy trap into local minimum points, this paper designs an improved BP neural network system. In order to improve the network convergence rate and reduce the training error, this paper optimizes the initial connecting weight value of neural network by the use of ant colony algorithm and trains artificial neural network by Levenberg-Marquardt algorithm.

针对常规BP神经网络参数的经验式取值方法以及收敛速度慢，容易陷入局部最小点等缺陷，设计了一种改进的神经网络系统，利用蚁群算法优化神经网络连接权初值，并采用LM算法对人工神经网络进行训练，提高了网络的收敛速度，降低了训练误差。

At first, with the low-frequency data measured, three of the LRE fault detection systems for the real-time condition are proposed using the nonlinear identification technology of the BP neural network, the state estimation technology of the dynamic neural network, and the pattern recognition technology of the fuzzy hypersphere neural network. The learning algorithms of the BP and dynamic neural network are researched at the same time. Furthermore, while the engine operation is divided into the start and steady-state processes, the real time ability, the response time, the accuracy, the robustness, the sensitivity and the monitoring parameter optimization are studied. In the test data analyses of the YF-75 engine, the detection system correctly carried out for all normal tests, and in the three abnormal tests the engine faults were accurately forecasted.

首先，基于低频测量数据，采用BP神经网络的非线性辨识技术、动态神经网络的状态估计技术及模糊超球神经网络的模式识别技术，提出了三种发动机故障实时检测系统；同时研究了BP神经网络和动态神经网络的学习算法；另外还把发动机工作分为启动过程和稳态过程，分别讨论了神经网络故障检测系统的实时性、及时性、准确性、鲁棒性、敏感性及参数优化问题；在YF-75发动机试车数据分析中，不仅全部正确地监测了正常试车过程，而且准确地预报了三次异常试车中的发动机故障。

The penalty optimal brain surgeon is a post-training algorithm and it has extreme high complexity. The OBS oriented compute model implemented neural network training and OBS pruning simultaneously, by taking the OBS pruning case as a penalty term of neural network objective functions based on optimized structure of the regularization method included in the neural network training process. It both maintained the OBS's accuracy and had regularization method's high efficiency. Raised the generalization of neural network model.

最优脑外科过程是一种训练后网络剪枝算法，计算的复杂度非常高，通过把剪枝条件以惩罚项的形式纳入神经网络的训练目标函数中，把正则化方法的结构优化蕴涵于网络训练过程，构建面向最优脑外科过程的计算模型，实现网络训练过程和最优脑外科过程并行剪枝，既保持了最优脑外科过程的准确性，又具有正则化的高效性，提高了神经网络模型的泛化性能。

Putt your way through 36 fun-filled holes of minigolf on 3D designed courses with elevated greens, bunkers, bridges and water hazards, among other crazy obstacles.

您的推杆方式，通过36个有趣的填孔迷你的三维设计的课程，以提升绿党，掩体，桥梁和水的危害，除其他疯狂的障碍。

Some participles can be used either as attributes or as predicatives.

有些分词既可当定语用，也可当表语用。