基于AMFNN的非线性噪声消除器

提出基于加乘性模糊神经网络(AMFNN)的非线性噪声消除器，讨论了AMFNN模型和学习算法及其通用逼近性．该消除器利用AMFNN逼近噪声，然后从测量信号中消去噪声即得到有用信号．该噪声消除器具有神经网络分布式并行信息处理能力、较好的容错性和鲁棒性以及除噪性能．     

铁路枢纽作业轮廓计划优化模型及算法

本文给出铁路枢纽日常运输组织工作轮廓计划多商品时空网络流模型及算法，对次日枢纽内大小车流、机车应用配合我纽内各站装、卸、排空计划作出合理安排。揭示枢纽内各站次日工作的重点与关键。为进一步编制日班计划及阶段计划提供指导及辅助决策基础。     

神经网络在车辆半主动控制中的应用

针对车辆半主动悬挂模型的非线性特性，研究了采用神经网络的自适应控制在车辆悬挂半主动控制中的应用，设计了采用前馈神经网络的辩识器和控制器，对控制器网络采用的学习规则进行了分析。仿真计算表明，采用神经网络自适应控制方法能有效改善车辆的平稳性，采用的神经网络辩识器和控制器的改进BP算法是有效的。     

IP ADDRESS AUTOCONFIGURATION FOR WIRELESS AD HOC NETWORKS

IntroductionWireless ad hoc networks are gaining increas-ing popularity in recent years because of their easeof deployment. No wired base station or infras-tructure is supported,and each hostcommunicatesone anothervia packetradios. In ad hoc networks,routing protocols are challenged with establishingand maintaining multihop routes in the face of mo-bility,bandwidth limitation and power con-straints. In ad hoc networks,each node( host)acts as a router since routes are mostly multihop.Nodes in …     

Practicability study on the suitability of artificial,neural networks for the approximation of unknown steering torques

For steer-by-wire systems, the steering feedback must be generated artificially due to the system characteristics. Classical control concepts require operating-point driven optimisations as well as increased calibration efforts in order to adequately simulate the steering torque in all driving states. Artificial neural networks (ANNs) are an innovative control concept; they are capable of learning arbitrary non-linear correlations without complex knowledge of physical dependencies. The present study investigates the suitability of neural networks for approximating unknown steering torques. To ensure robust processing of arbitrary data, network training with a sufficient volume of training data is required, that represents the relation between the input and target values in a wide range. The data were recorded in the course of various test drives. In this research, a variety of network topologies were trained, analysed and evaluated. Though the fundamental suitability of ANNs for the present control task was demonstrated.     

移动Ad Hoc网络中基于可靠传输的节能机制

随着移动Ad Hoc网络的应用日趋广泛,如何有效节省移动节点的能量,提高网络生存时间成为了难题.针对现有的节能协议和机制很少考虑链路误码率的问题,分析了在端到端重传机制和逐跳重传机制下的理想能耗,定义了新的链路代价函数.仿真结果表明使用该机制的路由协议具有较好性能,在数据传输可靠性和能耗之间达到有效的平衡.     

Simulation and Analysis of Typical Mobile Radio Channels

In this paper, the bit error rate (BER) performance for typical mobile radio channels is simulated and analyzed based on a tapped delay line model. The investigation is focused on the propagation environments determined by the average delay profile and the Doppler spectra. The profile characteristics and their influences on channel behavior are also examined.     

一种基于神经网络的馈线自适应继电保护技术

针对常规保护的自适应能力及检测某些复杂故障方面存在一定局限性,利用前馈神经网络,导出了常规保护与神经网络参数间的显式关系,证明了神经网络继电保护可实现常规馈线保护的功能。     

蜂窝移动通信系统中信道借用指配策略的优化

分析了蜂窝移动通信系统信道指配策略中的一个重要策略－信用策略,包括最早出现的简单借用策略,到后来在此基础上发展而来的带信道序号的借用策略（ＢＣＯ）和带方向锁定的借用策略（ＢＤＣＬ）。在原指配策略的基础上,增加了共道信道中的被锁定信道在信道表中的位置和处理,澄清了原策略中在这一点上的模糊不清。同时,通过两个方面的措施优化了ＢＣＯ和ＢＤＣＬ算法,仿真结果表明优化的算法可以显著降低原算法的复杂性。     

模糊神经网络系统在滩海铺管敷缆船中的应用设计

针对滩海铺管敷船数学模型过于复杂,难以用传统控制进行建模的特点,提出了用模糊神经网络进行智能化控制的方案,并采用了一种较为简单实用的全局最优算法简化计算过程。实验证明,此控制系统具有较强的自适应性与自学习能力,表明了该方案的正确性与实用性。