一个矢量形式的双圆弧插值算法

本文在分析数控插补最常用的双圆弧插值算法特点的基础上，将以局部坐标系中的三角运算为核心的传统双圆弧插值算法，改造成为以整体坐标系中的线性运算为核心的矢量形式的双圆弧插值算法，从而减少了计算的复杂性和程序的复杂性，提高了效率和可靠性。     

模糊Petri网及知识表示

在建造专家系统中虽然有很多种知识表示方法，但都有不尽人意的地方，本文试图用一种新的方法－Ｐｅｔｒｉ网模型来表示知识。本文给出了Ｆｕｚｚｚｙ Ｐｅｔｒｉ网和广义Ｆｕｚｚｙ Ｐｅｔｒｉ网两种模型，并给出了相应的推理算法，一旦专家知识用Ｐｅｔｒｉ网表示后，根据Ｐｅｔｒｉ网固有的特性，我们就能处理专家系统中并行推理、无回溯推理，反向推理等问题。     

In the theory of blast waves

The behavior of the blast wave from an exploding spherical volume is investigated mathematically over the entire range of blast-wave propagation. The computational method uses analytical results for a similar problem for a point explosion with counter pressure and the theory of an asymptotically equivalent point explosion. The asymptotic solution of the gas-dynamic equations away from the explosion site is matched to the initial conditions of blast-wave formation due to the disintegration of the detonation shock upon its arrival at the boundary of the exploding volume. The spatial distribution of the blast-front pressure is found for combustible gaseous systems and solid explosives. The theoretical results obtained agree quantitatively with available experimental measurements. __________ Translated from Fizika Goreniya i Vzryva, Vol. 42, No. 4, pp. 93–99, July–August, 2006.     

A frame-based knowledge representation model and its mapping to nested relations

The first part of this paper introduces the basic constructs of a frame representation model and gives a formal definition for them. Subsequently the nested relational model (NF²) is described as an extension of the classical relational model to support relation-valued attributes. In the second part of this paper both models are compared with each other and a mapping of frame representation structures to NF² structures is specified. The structural similarities between frames and NF² relations are made clear and it is shown that their main difference is due to the type polymorphism introduced by the concept hierarchy of the frame model. This causes type collisions to occur in the strictly typed NF² model when frames are directly mapped to NF² structures. Two solutions to this problem are suggested and compared. The paper concludes with a reformulation of query operations of the frame model in terms of NF² algebra operations.     

A hierarchical model for structure learning based on the physiological characteristics of neurons

Almost all applications of Artificial Neural Networks (ANNs) depend mainly on their memory ability. The characteristics of typical ANN models are fixed connections, with evolved weights, globalized representations, and globalized optimizations, all based on a mathematical approach. This makes those models to be deficient in robustness, efficiency of learning, capacity, anti-jamming between training sets, and correlativity of samples, etc. In this paper, we attempt to address these problems by adopting the characteristics of biological neurons in morphology and signal processing. A hierarchical neural network was designed and realized to implement structure learning and representations based on connected structures. The basic characteristics of this model are localized and random connections, field limitations of neuron fan-in and fan-out, dynamic behavior of neurons, and samples represented through different sub-circuits of neurons specialized into different response patterns. At the end of this paper, some important aspects of error correction, capacity, learning efficiency, and soundness of structural representation are analyzed theoretically. This paper has demonstrated the feasibility and advantages of structure learning and representation. This model can serve as a fundamental element of cognitive systems such as perception and associative memory.     

论科技论文英语摘要的表现形式

论述科技论文中英语摘要的文体风格、时态、语态和基本要求，并结合例句介绍了常用的表现形式，使之简洁、准确和流畅。     

基于Curvelet变换的多次波去除技术

本文基于波动方程的自由表面多次波压制预测减去法,采用近期迅速发展的多尺度变换系统中的Curvelet变换替代减去法,收到了较好的效果。该变换具有最优稀疏约束条件,能使一次波在一组基函数上的投影能量尽可能小。其主要实现过程为:对地震记录数据进行Curvelet变换,以预测多次波的Curvelet域的系数为阈值,采用类似去噪的手段去除多次波。该方法能满足去除多次波过程的能量最小准则。文中在Curvelet算法数值实验中尝试了先把地震记录做Radon变换,并用Curvelet阈值法减去Radon域的多次波,再把去除了多次波的数据做反Radon变换即为多次波去除结果。数值实验结果表明,在Radon域进行Curvelet变换去除多次波的效果更好,并能更好地保留一次波的能量。