Iterative Decoding of Parallel Concatenated Block Codes and Coset Based MAP Decoding Algorithm for F24 Code

A multi dimensional concatenation scheme for block codes is introduced, in which information symbols are interleaved and re encoded for more than once. It provides a convenient platform to design high performance codes with flexible interleaver size. Coset based MAP soft in/soft out decoding algorithms are presented for the F24 code. Simulation results show that the proposed coding scheme can achieve high coding gain with flexible interleaver length and very low decoding complexity.

CONVERGENCE OF IMPLICIT ITERATIVE PROCESS WITH ERRORS FOR A FINITE FAMILY OF ASYMPTOTICALLY NONEXPANSIVE MAPPINGS

The purpose of this article is to study the weak and strong convergence of implicit iteration process with errors to a common fixed point for a finite family of asymptotically nonexpansive mappings and nonexpansive mappings in Banach spaces. The results presented in this article extend and improve the corresponding results of [1, 2, 4-9, 11-15].

ON PROBLEM OF NEAREST COMMON FIXED POINT OF NONEXPANSIVE MAPPINGS

The purpose is by using the viscosity approximation method to study the convergence problem of the iterative scheme for an infinite family of nonexpansive mappings and a given contractive mapping in a reflexive Banach space. Under suitable conditions, it was proved that the iterative sequence converges strongly to a common fixed point which was also the unique solution of some variational inequality in a reflexive Banach space. The results presented extend and improve some recent results.

一种基于PCA/SOFM混合神经网络的图象压缩算法

鉴于用神经网络实现图象压缩是一种非常有效的方法,为此提出了一种基于PCA/SOFM混合神经网络的图象压缩编码算法,并对SOFM网络学习参数的优化进行了探讨.实验证明,与PCA+SOFM连续编码算法和基本SOFM算法相比,这种混合编码算法,由于占用存储空间少,因而降低了码书设计的计算量,并改善了码书的性能.

基于拓扑优化的平面2-DOF柔顺并联机构构型设计

目的运用拓扑优化技术设计一种平面2-DOF(Degrees-of-Freedom)柔顺并联机构,使其具有微米级别的微运动特性。方法依据平面2-DOF并联原型机构的受力情况进行运动特性分析,基于同构封闭矢量映射原理构建平面2-DOF柔顺并联机构的微分运动Jacobian矩阵,表达多自由度的柔顺并联机构从输入到输出间各关节的运动关系。定义柔度为优化目标函数,微分运动Jacobian矩阵为运动条件,材料体积分数为约束条件,构建平面2-DOF柔顺并联机构材料属性的有理近似模型,并运用移动渐进线法优化求解。结果优化后的平面2-DOF柔顺并联机构构型在x方向的位移为-0.0089mm,在y方向的位移为0.0053 mm,同时,其沿x方向和y方向的微位移理论值为-0.0031 mm和0.0067 mm。结论与并联原型机构的运动特性相比,平面2-DOF柔顺并联机构优化后的微运动特性具有一致性,均为微米级。

THE EXISTENCE AND UNIQUENESS OF SOLUTION FOR A CLASS OF STOCHASTIC FUNCTIONAL EQUAFIONS ON S.P.SPACE

This paper is concerned with the existence and uniqueness of solution for a class of stochastic functional equation: X =φ(X), where φ: B → B and B is a Banach space consisted of all left-continuous, (■_t)-adapted processes. Also, the main result is applied to some S.D.E (or S.I.E.). And the authors adopted some of the results in current research in the models of stochastic control recently. This paper proves the ekistence and uniquence and uniqueness of solution for stochastic functional equation. A series of corollaries are deduced from the special examples of the theorems in this paper.

基于PCA-SOFM模型的岩爆烈度等级预测

岩爆受多种条件因素影响,需要岩爆预测指标体系的完整性。取弹性变形能指数W_(et)、应力系数σ_(θ)/σ_(c)、脆性系数σ_(c)/σ_(t)、单轴抗压强度σ_(c)、单轴抗拉σ_(t)和围岩切向应力σ_(θ)等指标构建岩爆倾向性预测指标体系。采用主成分分析(PCA)法对指标降维处理、提取指标数据主要信息,得到3个线性无关的主成分输入向量。将处理后的指标作为输入向量对3种不同自组织特征映射神经网络(SOFM)模型进行训练与测试,比较3个模型的方差和竞争层神经元聚类效果,得到输出层神经元个数为16的最优预测模型。最后引入12组国内外工程实例与多维正态云模型、模糊综合评价法、灰类白化权函数聚类法、Russense判据所预测的岩爆烈度等级进行比较,研究表明:基于PCA-SOFM岩爆烈度等级预测结果与工程实际情况吻合度高,可行性较好,为岩爆烈度等级预测提供一种新的研究方法。

Some Geometric Properties of the m-Möbius Transformations

Möbius transformations, which are one-to-one mappings of onto have remarkable geometric properties susceptible to be visualized by drawing pictures. Not the same thing can be said about m-Möbius transformations fm mapping onto . Even for the simplest entity, the pre-image by fm of a unique point, there is no way of visualization. Pre-images by fm of figures from C are like ghost figures in Cm. This paper is about handling those ghost figures. We succeeded in doing it and proving theorems about them by using their projections onto the coordinate planes. The most important achievement is the proof in that context of a theorem similar to the symmetry principle for Möbius transformations. It is like saying that the images by m-Möbius transformations of symmetric ghost points with respect to ghost circles are symmetric points with respect to the image circles. Vectors in Cm are well known and vector calculus in Cm is familiar, yet the pre-image by fm of a vector from C is a different entity which materializes by projections into vectors in the coordinate planes. In this paper, we study the interface between those entities and the vectors in Cm. Finally, we have shown that the uniqueness theorem for Möbius transformations and the property of preserving the cross-ratio of four points by those transformations translate into similar theorems for m-Möbius transformations.

Convergence theorem of common fixed points for Lipschitzian pseudo-contraction semi-groups in Banach spaces

The purpose of this paper is to study the weak convergence problems of the implicity iteration process for Lipschitzian pseudocontractive semi-groups in the general Banach spaces. The results presented in this paper extend and improve the corresponding results of some people.

A Kind of Boundary Value Problems for Stochastic Differential Equations

In this paper we discuss stochastic differential equations with a kind of periodic boundary value conditions（in sense of mean value）. Appealing to the decomposition of equations, the existence of solutions is obtained by using the contraction mapping principle and Leray-Schauder fixed point theorem, respectively.

Migration of Magnetotelluric Data in Two——Dimensional Model

Since the wave equation of magnetoteiluric (MT)field is similar to the one of seismic , the migration techniques used in seismic can be applied to MT data . In this paper we make use of the principle of reflector mapping (i. e. U/D imaging principle ) to image MT data . That is, the MT wavefield observed on the surface of the earth can be resolved into upgoing and downgoing waves , the waves are extrapolated downward by the phase - shift method or the phase - shift plus interpolation (PSPI )method . Conductivity interfaces of the medium could be found by using the time coincidence of the upgoing and downgoing waves . Theoretical calculations show that the migration technique of MT data presented here is very effective . It can not only enhance the lateral resolution of MT data , but also obtain the visual image of subsurface interfaces . As compared with the conventional 2 - D inversion , this procedure is more simple in calculation and can be easily put into practice on a personal computer and is able to obtain the MT depth section , which is similar to seismic section .

A Hopfield Neural Network Algorithm for Automatic Name Placement for Point Feature

This paper presents a method of adding label to the map especially for the point feature. This method overcomes the shortcoming of traditional methods, e.g. Conflict\|Backtracking method. Its kernel algorithm use the hopfield neural network to find the best label position for point feature. The experimental results proves that this algorithm has good permanence and high speed.

Existence and Uniqueness of Positive (Almost) Periodic Solutions for a Neutral Multi-Species Logarithmic Population Model with Multiple Delays and Impulses

In this paper, by using the contraction mapping principle and constructing a suitable Lyapunov functional, we established a set of easily applicable criteria for the existence, uniqueness and global attractivity of positive periodic solution and positive almost periodic solution of a neutral multi-species Logarithmic population model with multiple delays and impulses. The results improve and generalize the known ones in [1], as an application, we also give an example to illustrate the feasibility of our main results.

Asymptotic Stability of Singular Solution for Camassa-Holm Equation

The aim of this paper is to study singular dynamics of solutions of Camassa-Holm equation. Based on the semigroup theory of linear operators and Banach contraction mapping principle, we prove the asymptotic stability of the explicit singular solution of Camassa-Holm equation.

基于PCA/SOFM混合神经网络的矢量量化

针对自组织特征映射(SOFM)神经网络应用于矢量量化具有收敛速度慢、计算量大等缺点,本文提出了一种基于PCA/SOFM混合神经网络的矢量量化的算法,先用主元分析(PCA)线性神经网络对输入矢量进行降维处理,再用SOFM神经网络进行矢量量化。通过调整SOFM神经网络的学习函数、邻域权值及初始码书对网络进行优化。实验表明,改进算法缩短了图像压缩的时间,提高了码书的性能。

思维导图在数学单元复习教学中的应用探析

思维导图既是一种高效且直观的思维工具,也是提升学生数学核心素养的辅助手段。思维导图在数学单元复习教学中的应用价值是多方面的,它不仅能够帮助学生系统化地整合知识、强化记忆与理解,还能够提高学生的综合能力,方便他们进行复习与自查。文章阐述思维导图在数学单元复习教学中的应用价值,分析思维导图在数学单元复习教学中的应用原则,探讨思维导图在数学单元复习教学中的应用策略,旨在优化复习教学过程,培养学生的自主学习能力、思维能力和问题解决能力。

遥感图像的MAP超分辨重建

遥感根本目的就是获得清晰的高空间分辨率的图像,从而可以进一步地分析处理。为了在遥感测量中获得更高空间分辨率、更高信噪比、更清晰的图像,本文对图像处理领域超分辨算法进行了研究。建立了一套拟合模拟现实的成像系统模型,在这种模型的基础之上,利用最大后验概率系统理论,讨论了现实情况中的运动模糊,噪声等情况,改进了MAP超分辨算法。实验结果表明:使用本文改进的基于MAP理论的Markov随机场约束的多帧超分辨重建算法,可以较好提高超分辨效果,与三次立方插值方法相比,PSNR至少提高约5.1dB左右,与未改进的MAP方法相比,PSNR提高约0.2dB左右。本文提出了动态的先验约束方法,给约束函数添加与迭代次数相关的约束项,该改进创新可以加快收敛并且更加逼近真实图像,实验表明该方法收敛速度更快,约束效果良好,更适合实际应用。

Large Scale VLSI Module Placement Using LFF Heuristics by Stages

We present a deterministic algorithm for large-scale VLSI module placement. Following the less flexibility first （LFF） principle,we simulate a manual packing process in which the concept of placement by stages is introduced to reduce the overall evaluation complexity. The complexity of the proposed algorithm is （N1 ＋ N2 ） × O（ n^2 ） ＋ N3× O（n^4lgn） ,where N1, N2 ,and N3 denote the number of modules in each stage, N1 ＋ N2 ＋ N3 = n, and N3〈〈 n. This complexity is much less than the original time complexity of O（n^5lgn）. Experimental results indicate that this approach is quite promising.

Arbitrary Rectilinear Block Packing Based on Less Flexibility First Principles

The definition and formula of flexibility of arbitrary rectilinear blocks are introduced and LFF principles are extended to handle arbitrary rectilinear blocks and blocks with relative constraints.The experimental results demonstrate the efficiency and effectiveness of the proposed method.