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Techniques of parallelizing object oriented language have had great progress in recent years.

近年来,面向对象语言的并行化技术取得了许多重要进展。

The result of this research has been applied to a real optimizing and parallelizing compiler for a SIMD chip.

本文的工作结果已经应用到一个实际的SIMD芯片的优化/并行化编译器中。

In the parallel program, the in-core and out-of-core algorithms can be identified and chosen to use automatically. So the algorithms are united.(3) The re-orthonormalization technique is used to solve the loss of orthonormality of basis vector during the classical GMRES method solving large-scale three dimensional elasto-static BE problems.

3采用重正交技术解决了经典GMRES方法在求解大型三维弹性静力边界元问题过程中出现的基向量正交性丧失的问题;结合边界元基本解和系数矩阵的特点以及并行化的要求,研究了几种预条件技术;并以重正交技术和预条件技术实现了经典GMRES的实用化。

The study of parallelism for Java program is one of the most important subjects at present.

Java程序的并行化研究是一个重要课题。

Because of its unique characteristics such as being flexible, easy to implement, and parallelizable, and being efficient for processing nonlinear problems, particle filter becomes a new and very promising hot topic in applied statistics, signal processing, and artificial intelligence communities.

因其具有灵活、易於实现、并行化等特点,成为统计学、信号处理、人工智能等领域新的研究热点,并被广泛地应用於目标跟踪等领域中。

ABSTRACT Particle filter is a new real time inference algorithm which is based on Bayesian inference and Monte carlo method. Because of its unique characteristics such as flexible, easy to implement, parallelizable, extensive applicability and efficient to process nonlinear problems, particle filter has been paid more and more attention in recent years and becomes a new and very promising hot topic in applied statistics, signal processing, automatic control, artificial intelligence and machine learning communities. At the same time, the formidable increasing computational power and some recent developments in applied statistics and probability theory has stimulated many advances in this field.

始于20世纪90年代初的粒子滤波器技术是一种基于贝叶斯推理和蒙特卡罗方法的实时在线推理算法,因其具有灵活、易于实现、并行化、应用前景广阔以及有效处理非线性问题等特点,受到了越来越广泛的重视,成为统计学、信号处理、自动控制、人工智能、机器学习等领域新的研究热点,同时伴随着计算机计算能力的超指数增长以及应用统计学、概率论等一些学科的不断进步,使该领域的研究得到了迅速发展。

It was proposed that a robust and efficient parallelizable preconditioner for solving general sparse linear systems of equations, in which the use of sparse approximate inverse techniques in a multi-level block ILU preconditioner wereinvestigated.

设计了一种求解一般稀疏线性方程组的健壮且有效的可并行化预条件子,这种预条件子涉及在多层块ILU预条件子中使用稀疏近似逆技术。

One of the prominent characteristics of the self-learning neuron is thatit has a forward-channel, a backward-channel and a leamer, This makes each neuron in a self-learning BP network accomplish the forward propagation of message, backward propagation of errors, and modification of its parameters independently, and hence makes the network implement parallel computing easity.

由自学习神经元组成的自学习BP网络可以真正做到正向传播信息、反向传播误差及学习的并行化

It provide some interfaces to query and operate window state,which is useful for parallel integration.

针对软件并行化集成的需要,提供了一套窗体状态查询和控制接口。

It is used to manage the information in whole the life cycle of software and create parallel cooperative design and manufacture environment in the enterprise.

它可以对产品整个生命周期的信息进行管理,在企业范围内为产品设计与制造建立并行化的协作环境。

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