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.     

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.     

基于神经网络非线性系统辨识和控制的研究

本文提出了由静态的前馈网络和稳定的滤波器构成的非线性系统的辨识模型，在神经网络固有的逼近误差存在的情况下，从理论上讨论了神经网络应用于辨识控制过程中系统的稳定性问题，最后研究了在非线性系统的轨迹跟踪过程中增加滑动控制来偿神经网络的逼近误差，从而提高系统跟踪性能。     

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.     

Perceptually Grounded Language Learning: Part 2—DETE: A Neural/Procedural Model

In Part 1 of this two-part series, we introduced Katamic memory—a neural network architecture capable of robust sequence learning and recognition. In Part 2, we introduce the Blobs World taskjdomain for language learning and describe the DETE language learning system, which is composed of over 50 Katamic memory modules. DETE currently learns small subsets of English and Spanish via association with perceptual! motor inputs. In addition to Kaiamic memory, DETE employs several other novel features: (1) use of feature planes, to encode visual shapes, spatial relationships and the motions of objects, (2) phase-locking of neural firing, in order to represent focus of atention and to bind objects across multiple feature planes, and (3) a method for encoding temporal relationships, so that DETE can learn utterances involving the immediate past and future. We compare DETE to related models and discuss the implications of this approach for language-learning research.     

Artificial intelligence and symbols

The introduction of massive parallelism and the renewed interest in neural networks gives a new need to evaluate the relationship of symbolic processing and artificial intelligence. The physical symbol hypothesis has encountered many difficulties coping with human concepts and common sense. Expert systems are showing more promise for the early stages of learning than for real expertise. There is a need to evaluate more fully the inherent limitations of symbol systems and the potential for programming compared with training. This can give more realistic goals for symbolic systems, particularly those based on logical foundations.     

Environmentally friendly, heterogeneous acid and base catalysis for the methylation of catechol: Chances for the control of chemo-selectivity

The properties of catalysts with (i) Brønsted-type acidity (H-mordenite and Al/P mixed oxide), (ii) Lewis-type acidity (Al trifluoride) or (iii) basic characteristics (Mg/Fe mixed oxide) were investigated in the gas-phase methylation of catechol. When methanol was used as the methylating agent, H-mordenite and AlF₃ gave high selectivities to guaiacol (the product of O-methylation) under mild reaction conditions, that is at very low catechol conversions. An increase in temperature led to the transformation of guaiacol to phenol and cresols, and to considerable catalyst deactivation. The basic catalyst Mg/Fe/O also favored an extensive degradation of guaiacol to phenol. On the mildly acidic catalyst Al/P mixed oxide a stable catalytic performance and a high selectivity to guaiacol at 40% catechol conversion were obtained. When methylformate, a more reactive methylating agent, was used with AlF₃ and Mg/Fe mixed oxide as catalysts, higher catechol conversions and slower deactivation rates could be achieved under mild reaction conditions, with a low extent of guaiacol degradation. However, methylformate rapidly decomposed when temperatures above 350 °C were used. Finally, tests were made by reacting catechol and diethoxymethane with acid catalysts, with the aim of synthesizing methylenedioxybenzene. The latter product was obtained with high selectivity, but with very low yield, due to both catalyst deactivation and decomposition of diethoxymethane.