基于免疫算法的Hopfield神经网络多用户检测器

提出的基于免疫算法的Hopfield神经网络多用户检测器，将扰乱的Hopfield神经网络多用户检测器的输出作为免疫算法的初始种群，利用了免疫算法的全局收敛的特点，从而克服了Hopfield易收敛到局部能量最小点的缺点。理论分析和仿真结果表明：该检测器具有良好的抗多址干扰和抗远近效应的能力。     

光纤光栅视觉系统

利用光学衍射原理，研制成了光纤光栅衍射屏，并与计算机神经网络相结合，开发了了一种识别立体形状的视觉系统。本文介绍了光纤光栅的设计原理及计算方法，给出了系统的总体结构及工作原理，完成了三棱 柱，三棱锥、四棱柱，四棱锥和球等立体形状学习与识别，并讨论了实验结果。     

日本关西宽带实验网印象

本文根据实地考察内容，结合宽带网络技术和业务重点及实施策略，全面介绍了日本关西宽带实验网发展背景，通信与广播电视综合应用实验和Ｂ－ＩＳＤＮ实用化实验的进展以及ＮＴＴ所起作用。文章最后就关西宽带实验网的借鉴意义提出了几方面意见。     

运用接入新技术,组建农村用户接入网

运用接入新技术组建农村用户接入网已势在必行。本文针对我国经济水平低、地区间发展不平衡等实际情况，对组建我国农村用户接入网的有关策略进行了论述。     

K终端可靠度分解算法中多边形→链简化定理的完善

无向网络K终端可靠度的分解算法中,包括多边形→链简化在内的等可靠度简化和分解定理结合,可以降低算法的复杂度。本文完善了边随机无向网络和混合随机无向网络的4#,6#,7#型多边形→链简化定理。计算机编程验证了其正确性。     

Impact of QOS requirements on video coding for ATM networks

The broadband integrated services digital networks (B-ISDN) based on asynchronous transfer mode (ATM) technology can support a wide range of applications such as voice, video, still images, and data. Compression techniques increase the effective bandwidth utilization, but the bursty and asynchronous nature of the traffic can still lead to congestion in the network, and degradation of image quality and quality of service (QOS). Some of the features to provide better coding schemes for ATM networks are layered coding, resynchronization, buffering, interleaved schemes, constrained bit rate due to buffers, encapsulation with the RTP or AAL1 for clock recovery, lapped transforms, motion compensation, and optimal bit allocation for coders based on wavelet transforms. We review various techniques forimage and video coding such as transforms, motion compensation, vector quantization, and subband coding. We outline the impact of the cell loss ratio (CLR), delay and cell delay variation (CDV) on video coding: blocking effects, loss of frame synchronization, motion vectors, and vector quantization codewords. The open problems include tuning coding parameters to the available QOS provided by the network.     

人造参考星系统设计

简述了人造参考星系统，并用该系统作为大型望远镜主动光学和自适应光学的Ｓｈａｃｋ－Ｈａｒｔｍａｎ波面探测系统的光源。     

An intelligent sensor for detection of milling chatter

In this paper, a new real-time sensor system has been developed to detect chatter in milling operations. In the developed sensor system, a pattern recognition technique based on an unsupervised neural network using the adaptive resonance theory (ART) is adopted for detection of milling chatter. The features on the cutting force spectrum are fed into the sensor system to classify the milling process with or without chatter. The experimental results indicate that the proposed sensor system can accurately detect milling chatter regardless of the variation in cutting conditions.     

Aeromagnetic compensation using neural networks

Airborne magnetic surveys in geophysical exploration can be subject to interference effects from the aircraft. Principal sources are the permanent magnetism of various parts of the aircraft, induction effects created by the earth's magnetic field and eddy-current fields produced by the aircraft's manoeuvres. Neural networks can model these effects as functions of roll, pitch, heading and their time derivatives, together with vertical acceleration, charging currents to the generator, etc., without assuming an explicit physical model. Separation of interference effects from background regional and diurnal fields can also be achieved in a satisfactory way.     

Technical Note: Selecting a Classification Method by Cross-Validation

If we lack relevant problem-specific knowledge, cross-validation methods may be used to select a classification method empirically. We examine this idea here to show in what senses cross-validation does and does not solve the selection problem. As illustrated empirically, cross-validation may lead to higher average performance than application of any single classification strategy, and it also cuts the risk of poor performance. On the other hand, cross-validation is no more or less a form of bias than simpler strategies, and applying it appropriately ultimately depends in the same way on prior knowledge. In fact, cross-validation may be seen as a way of applying partial information about the applicability of alternative classification strategies.