基于相关性分析的多模式多视点视频编码

多视点视频编码方法除需具有较高编码效率外,还必须支持视点或时间的随机访问、低延时编解码、视点可分级等性能.多视点视频信号的时间、视点间相关性随相机密度、光照、对象运动等因素不同而变化.文中提出基于多视点视频信号相关性分析的多模式多视点视频编码方法,改变传统单一预测模式的多视点编码结构,将多种性能优良的预测编码模式有机结合,根据多视点视频相关性分析灵活选择合适的预测编码模式,以获得优异的编码综合性能.实验结果表明,所提出的多模式多视点视频编码方法在保证高压缩效率的前提下,可进一步降低复杂度,提高随机访问性能.     

基于H.264标准的多视点视频编码方案的研究

为研究一种新的高效的多视点视频编码方法,提高编码效率,并有效地提高视点间随机切换访问的能力,利用H.264中的新技术多参考帧、SP/SI帧、分层B帧编码等,根据时空预测编码结构的方法,提出了一种基于分层B帧并有利于视点间随机切换访问的多视点视频编码方案.实验结果表明,该方案在提高了编码效率的同时,在视点较多的情况下能够有效地提高视点间随机切换访问的能力.     

一种多视点视频系统中随机访问的解码路径计算新方法

在多视点视频系统中,用户端的随机访问性能是表征交互能力的一个重要指标。当用户进行随机访问时,需要快速确定相应的解码路径,以快速有效地获得相应视点与时刻的图像帧。针对H.264多视点视频系统中随机访问效率不高这个情况,分析了传统多视点视频系统随机访问解码路径的计算方法,讨论了其中存在的非最优解码路径问题,提出帧等级矩阵的概念。然后,提出针对HBP（hierarchical B pictures) 这种具有代表性的多视点视频编码预测结构的解码路径计算快速算法。实验结果表明,所提算法能获得较优解码路径,从而有效地提高随机访问性能,降低解码复杂度。     

高清视频编码芯片架构设计挑战及多目标性能评价模型

FPGA和ASIC是高清视频编码器较合适的实现平台,视频编码芯片架构设计面临着较多挑战,包括吞吐量巨大、外存带宽极高、硬件资源消耗大、数据依赖阻塞正常流水、多目标性能较难均衡等.高清视频编码芯片架构设计需和算法优化相结合,以实现多个目标参数之间均衡,如何评价硬件架构的多目标性能,是首先要解决的问题.在分析芯片架构设计面临挑战、典型关注的多目标性能基础上,提出多目标性能参数的度量方法,对多个目标参数进行合理映射和归一化处理,并首次提出多目标性能评价模型.基于此模型,对主流的高清H.264/AVC编码芯片架构的多目标性能进行了评价和比较.该研究对于优化H.264/AVC及新一代HEVC编码芯片架构有着重要的参考价值.     

支持空域随机访问的多视点视频编码方法

基于H.264/AVC编码框架,提出一种支持空域随机访问功能的多视点视频编码方法,以满足快速虚拟视点绘制的需求.首先采用灵活的GOP时空划分来构建独立时空体,从而在每个时空体内通过限制帧间预测范围来增强解码的独立性,实现压缩域内某一帧特定区域数据的快速定位;进而通过调整预测空间来改善空域随机访问和整帧编码性能之间的关系.实验结果表明,该方法不仅在整帧压缩效率和快速空域随机访问灵活性方面达到了很好的平衡,而且能够通过传输部分码流的方式节省传输带宽.     

一种改进预测结构的多视点视频编码

多视点视频编码是视频编码的研究热点之一。针对联合多视点视频编码（Joint Multi-view Video Coding,JMVC）采用的分层B帧预测结构编码复杂度高,随机访问性能较差等缺点,提出了一种改进的预测结构。所提出的预测结构对B视点中以前一帧作为其时间参考的帧仅采用时间预测,对所有P视点的非关键帧均不进行视点间预测,有效地降低了计算复杂度,提高了随机访问性能。通过选取合适的I视点位置,以减少结构简化带来的编码效率损失。实验结果表明,与分层B帧预测结构相比,所提出的预测结构在保证编码效率损失不大的情况下,显著降低了平均编码时间。改进的预测结构也具有更好的随机访问性能。     

不经意随机访问机研究综述

随着云计算与大数据技术的发展,隐私保护越来越受到人们的关注.加密是一种常见的保护数据隐私的方法,但是单纯地利用加密手段并不能抵抗所有类型的攻击.攻击者可以通过观察用户对数据的访问模式来推断隐私信息,其中包括数据的重要程度、数据的关联性,甚至是加密数据的内容等.不经意随机访问机是一种重要的保护访问模式的手段,它通过混淆每一次访问过程,使其与随机访问不可区分,从而保护真实访问中的访问操作、访问位置等信息.不经意随机访问机在安全云存储系统以及安全计算领域有着非常重要的作用.利用不经意随机访问机可以降低攻击者通过访问模式推测隐私信息的可能性,减小系统受到的攻击面,从而提供更安全更完整的服务.对不经意随机访问机的研究与应用进行综述,主要介绍了不经意随机访问机的相关概念以及设计方法,重点分析并总结了目前学术界研究的性能优化的常见策略及其优劣性,主要包括针对客户端与服务器的平均带宽与最坏情况带宽优化、存储开销优化以及交互轮数优化等方面.同时讨论了将不经意随机访问机应用于安全存储系统的一般性问题,如数据完整性保护以及支持多用户并发访问等,也讨论了将其应用于安全计算领域的问题,如安全计算协议设计以及不经意数据结构的设计等;最后,对不经意随机访问机未来的研究方向进行了展望.     

基于随机模型预测控制的插电式混合动力汽车 多目标能量管理策略

为了改善插电式混合动力汽车的燃油消耗和排放, 开展多目标随机模型预测控制策略的研究. 首先, 建立适用于模型预测的多元线性回归的发动机和电池模型, 建立融合燃油消耗和排放的多目标价值函数的模型预测控制, 随后, 基于随机驾驶员模型未来时刻的车速, 结合交通信息并利用动态规划(DP)算法进行参考电荷状态(SOC)优化, 进而建立多目标随机模型预测控制策略. 最后, 通过与DP, MPC等策略进行对比验证, 及给出两组不同权值进行多目标控制效果分析. 结果表明, 该策略的燃油消耗和排放最接近DP的控制效果, 且设置不同权重值可获得相应的控制目标, 说明该策略对提升燃油消耗和排放的多目标性能的有效性.     

随机时滞马尔可夫跳跃系统的比例-积分跟踪控制

针对具有时变时滞和未知非线性的随机马尔可夫跳变系统,基于传统的PI控制策略和线性矩阵不等式算法,提出一种具有随机稳定性能、跟踪性能和鲁棒性能的多目标控制器设计方案.运用Lyapunov稳定性理论并引入L<,1>性能指标,构造出具有PI结构的跟踪控制器,保证了随机马尔可大跳跃系统的稳定性和跟踪性能,实现了系统跟踪性能的优...     

几种随机接入协议的仿真性能比较分析

本文对纯ALOHA（P-ALOHA）、时隙ALOHA（S-AIDHA）和载波监听多路访问（CSMA）等三种随机接入协议的工作原理进行了介绍。对三种协议进行了理论分析,采用OPNET对协议进行了仿真性能比较,得出了相关重要结论,为提高随机接入协议性能提供了新的参考。     

Predictive control based on neural network models with I/O feedback linearization

This paper presents an approach for the constrained non-linear predictive control problem based on the input-output feedback linearization (IOFL) of a general non-linear system modelled by a discrete-time affine neural network model. Using the resulting linear system in the formulation of the original non-linear predictive control problem enables to restate the optimization problem as the minimization of a quadratic function, which solution can be found using reliable and fast quadratic programming (QP) routines. However, the presence of a non-linear feedback linearizing controller maps the original linear input constraints onto non-linear and state dependent constraints on the controller output, which invalidates a direct application of QP routines. In order to cope with this problem and still be able to use QP routines, an approximate method is proposed which simultaneously guarantees a feasible solution without constraints violation over the complete prediction horizon within a finite number of steps, while allowing only for a small performance degradation.     

基于约束条件随机场的Web数据语义标注

Web数据语义标注是Web信息抽取中的关键步骤.条件随机场是利用序列特征处理序列标注问题的经典方法.然而现有条件随机场模型无法综合利用已有的Web数据库信息和Web数据元素之间的逻辑关系,导致Web数据语义标注准确率不高.因此,提出一种约束条件随机场模型(CCRF).该模型通过引入可信约束和逻辑约束,有效利用了已有的Web数据库信息和Web数据元素之间的逻辑关系.为了克服现有条件随机场模型Viterbi推理方法无法综合利用这2类约束的不足,该模型采用整数线性规划推理方法,将两类约束同时引入推理过程.通过在多个领域的真实数据集上的实验结果表明,所提出的模型能够显著提高Web数据语义标注的性能,并且为Web信息抽取奠定了良好的基础.     

基于自适应参考帧模式选择的多视点视频编码方法

基于多视点视频序列相关性,提出独立片的概念,进而提出一种采用自适应参考帧模式选择的多视点视频编码方法.在保证高率失真性能的前提下,应用独立片、自适应算法有效地降低了多视点视频编码计算复杂度,将多种性能进行有机结合,可以根据用户外部设置的参数调整自适应模式.实验结果表明,该方法在保证高压缩效率的前提下,能有效地降低计算复杂度,并改善随机访问性能.     

Fuzzy random programming with equilibrium chance constraints

To model fuzzy random decision systems, this paper first defines three kinds of equilibrium chances via fuzzy integrals in the sense of Sugeno. Then a new class of fuzzy random programming problems is presented based on equilibrium chances. Also, some convex theorems about fuzzy random linear programming problems are proved, the results provide us methods to convert primal fuzzy random programming problems to their equivalent stochastic convex programming ones so that both the primal problems and their equivalent problems have the same optimal solutions and the techniques developed for stochastic convex programming can apply. After that, a solution approach, which integrates simulations, neural network and genetic algorithm, is suggested to solve general fuzzy random programming problems. At the end of this paper, three numerical examples are provided. Since the equivalent stochastic programming problems of the three examples are very complex and nonconvex, the techniques of stochastic programming cannot apply. In this paper, we solve them by the proposed hybrid intelligent algorithm. The results show that the algorithm is feasible and effectiveness.     

Genetic algorithm for balancing reconfigurable machining lines

We consider the problem of designing a reconfigurable machining line. Such a line is composed of a sequence of workstations performing specific sets of operations. Each workstation is comprised of several identical CNC machines (machining centers). The line is required to satisfy the given precedence order, inclusion, exclusion and accessibility constraints on the given set of operations. Inclusion and exclusion are zoning constraints which oblige or forbid certain operations to be performed on the same workstation. The accessibility constraints imply that each operation has a set of possible part positions under which it can be performed. All the operations performed on the same workstation must have a common part position. Workstation times are computed taking into account processing and setup times for operations and must not exceed a given bound. The number of CNC machines at one workstation is limited, and the total number of machines must be minimized. A genetic algorithm is proposed. This algorithm is based on the permutation representation of solutions. A heuristic decoder is suggested to construct a solution from a permutation, so that the output solution is feasible w.r.t. precedence, accessibility, cycle time, and exclusion constraints. The other constraints are treated with a penalty approach. For a local improvement of solutions, a mixed integer programming model is suggested for an optimal design of workstations if the order of operations is fixed. An experimental evaluation of the proposed GA on large scale test instances is performed.     

Computation of probabilistic linear programming problems involving normal and log-normal random variables with a joint constraint

A method for solving single- and multi-objective probabilistic linear programming problems with a joint constraint is presented. It is assumed that the parameters in the probabilistic linear programming problems are random variables, and the probabilistic problem is converted to an equivalent deterministic mathematical programming problem. In this paper the parameters are generally considered as normal and log-normal random variables. A non-linear programming method is used to solve the single-objective deterministic problem, and a fuzzy programming method is used to solve the multi-objective deterministic problem. Finally, a numerical example is presented to illustrate the methodology.     

多中继协作无线网络中基于随机线性网络编码的调度方案

为进一步提升多中继协作无线网络传输效率,本文提出一种基于随机线性网络编码的动态规划方案,以最小化重传次数为目标,综合考虑各中继节点的有效信息与链路传输可靠性,实现多中继协同转发,以提升传输有效性。在各转发链路相互独立的情况下,针对整个传输过程,自适应地选取状态转移路径,确定最优转发节点。仿真结果表明,本方案相比随机调度机制能显著提升平均吞吐量,减少重传次数。在降低对反馈信息依赖和减少反馈开销的同时,其性能皆逼近完全反馈下基于贪心算法的调度机制。     

Multi-objective decision making model under fuzzy random environment and its application to inventory problems

In this paper, we concentrate on developing a fuzzy random multi-objective model about inventory problems. By giving some definitions and discussing some properties of fuzzy random variable, we design a method of solving solution sets of fuzzy random multi-objective programming problems. These are applied to numerical inventory problems in which all inventory costs, purchasing and selling prices in the objectives and constraints are assumed to be fuzzy random variables in nature, and then the impreciseness of fuzzy random variables in the above objectives and constraints are transformed into fuzzy variables which are similar trapezoidal fuzzy numbers. The exact parameters of fuzzy membership function and probability density function can be obtained through fuzzy random simulating the past dates. By comparing the results with those from the fuzzy multi-objective models, we believe that the proposed fuzzy random multi-objective model and hybrid intelligent algorithm provide significant solutions to construct other inventory models with fuzzy random variables in real life.