A parallel memory architecture for video coding

To efficiently exploit the performance of single instruction multiple data （SIMD） architectures for video coding, a parallel memory architecture with power-of-two memory modules is proposed. It employs two novel skewing schemes to provide conflict-free access to adjacent elements （8-bit and 16-bit data types） or with power-of-two intervals in both horizontal and vertical directions, which were not possible in previous parallel memory architectures. Area consumptions and delay estimations are given respectively with 4, 8 and 16 memory modules. Under a 0.18-pm CMOS technology, the synthesis results show that the proposed system can achieve 230 MHz clock frequency with 16 memory modules at the cost of 19k gates when read and write latencies are 3 and 2 clock cycles, respectively. We implement the proposed parallel memory architecture on a video signal processor （VSP）. The results show that VSP enhanced with the proposed architecture achieves 1.28× speedups for H.264 real-time decoding.     

Novel algorithm for complex bit reversal: employing vector permutation and branch reduction methods

We present novel vector permutation and branch reduction methods to minimize the number of execution cycles for bit reversal algorithms. The new methods are applied to single instruction multiple data （SIMD） parallel implementation of complex data floating-point fast Fourier transform （FFT）. The number of operational clock cycles can be reduced by an average factor of 3.5 by using our vector permutation methods and by 1.1 by using our branch reduction methods, compared with conventional implementations. Experiments on MPC7448 （a well-known SIMD reduced instruction set computing processor） demonstrate that our optimal bit-reversal algorithm consistently takes fewer than two cycles per element in complex array operations.     

基于雷达成像的熵函数优化方法(英文)

对ISAR成像的最小熵自聚焦(MEA)算法进行了收敛性分析. 仿真结果表明, MEA算法存在局部最优问题, 作为其代价函数的ISAR像熵函数并非多维补偿相位的下凸函数. 只有当该补偿相位矢量的初值选取合适, 使其处于像熵函数的全局最小点附近时, MEA算法才能收敛到全局最优解. 针对MEA算法的最优化问题, 给出了一种基于雷达成像的熵函数优化方法. 该方法首先采用改进的多普勒中心跟踪法估计补偿相位初值. 该初值是最大似然准则下的估计结果, 可以使初始相位位于最优解附近. 然后, 利用快速MEA 算法进行局部搜索, 得到全局最优解. 仿真结果表明, 该算法不仅实现了MEA算法的全局最优求解, 还可避免步长、阈值等参数的选择与调整.     

Achieving Efficient Channel Utilization for Data Communications in IEEE 802.11 WLAN

In the IEEE g02. 11 protocol, the adoption of the exponential backoff technique leads to throughput performance strongly dependent on the initial contention window size and, most importantly, on the number of contending stations considered in the network. This paper proposes a simple but accurate method to dynamically estimate the number of contending stations in a wireless local area network （ WLAN ）. Based on estimation, all the mobile stations dynamically adjust the initial contention window in medium access control （ MAC ） layer to avoid collisions. The simulation results show that the proposed algorithm can achieve efficient channel utilization, higher system throughput, and better fairness performance.     

A spatially triggered dissipative resource distribution policy for SMT processors

Programs take on changing behavior at nmtime in a simultaneous multithreading （SMT） environment. How reasonably common resources are distributed among the threads significantly determines the throughput and fairness performance in SMT processors. Existing resource distribution methods either mainly rely on the front-end fetch policy, or make distribution decisions according to the limited information from the pipeline. It is difficult for them to efficiently catch the various resource requirements of the threads. This work presents a spatially triggered dissipative resource distribution （SDRD） policy for SMT processors, its two parts, the self-organization mechanism that is driven by the real-time instructions per cycle （IPC） performance and the introduction of chaos that tries to control the diversity Of trial resource distributions, work together to supply sustaining resource distribution optimization for changing program behavior. Simulation results show that SDRD with fine-grained diversity controlling is more effective than that with a coarse-grained one. And SDRD benefits much from its two well-coordinated parts, providing potential fairness gains as well as good throughput gains. Meanings and settings of important SDRD parameters are also discussed.     

Hybrid discrete particle swarm optimization algorithm for capacitated vehicle routing problem

INTRODUCTION The vehicle routing problem (VRP), which was first introduced by Dantzig and Ramser (1959), is a well-known combinatorial optimization problem in the field of service operations management and logis- tics. The capacitated vehicle routing problem (CVRP) is an NP-hard problem for simultaneously determining the routes for several vehicles from a central depot to a set of customers, and then return to the depot without exceeding the capacity constraints of each vehicle. In pr…     

Efficient timing and frequency offset estimation scheme for OFDM systems

A new training symbol weighted by pseudo-noise(PN) sequence is designed and an efficient timing and fre quency offset estimation scheme for orthogonal frequency division multiplcxing(OFDM)systems is proposed.The timing synchronization is accomplished by using the piecewise symmetric conjugate of the primitive training symbol and the good autocorrelation of PN weighted factor.The frequency synchronization is finished by utilizing the training symbol whose PN weighted factor is removed after the timing synchronization.Compared with conventional schemes,the proposed scheme can achieve a smaller mean square error and provide a wider frequency acquisition range.     

Reliability based multiobjective optimization for design of structures subject to random vibrations

Based on a multiobjective approach whose objective function （OF） vector collects stochastic reliability performance and structural cost indices, a structural optimization criterion for mechanical systems subject to random vibrations is presented for supporting engineer＇s design. This criterion differs from the most commonly used conventional optimum design criterion for random vibrating structure, which is based on minimizing displacement or acceleration variance of main structure responses, without considering explicitly required performances against failure. The proposed criterion can properly take into account the design-reliability required performances, and it becomes a more efficient support for structural engineering decision making. The multiobjective optimum （MOO） design of a tuned mass damper （TMD） has been developed in a typical seismic design problem, to control structural vibration induced on a multi-storey building structure excited by nonstationary base acceleration random process A numerical example for a three-storey building is developed and a sensitivity analysis is carried out. The results are shown in a useful manner for TMD design decision support.     

利用全景科学教学法进行主题教学的设计

作者在研究国内外的科学教学理论的同时 ,综合我国特殊儿童科学教育课程改革的现状 ,以“岩石”这一主题为例 ,阐述了利用全景科学教学法进行主题教学的设计过程 ,并提出了可操作的主题教学的方法。     

Robust design and optimization for autonomous PV-wind hybrid power systems

This study presents a robust design method for autonomous photovoltaic （PV）-wind hybrid power systems to obtain an optimum system configuration insensitive to design variable variations. This issue has been formulated as a constraint multi-objective optimization problem, which is solved by a multi-objective genetic algorithm, NSGA-II. Monte Carlo Simulation （MCS） method, combined with Latin Hypercube Sampling （LHS）, is applied to evaluate the stochastic system performance. The potential of the proposed method has been demonstrated by a conceptual system design. A comparative study between the proposed robust method and the deterministic method presented in literature has been conducted, The results indicate that the proposed method can find a large mount of Pareto optimal system configurations with better compromising performance than the deterministic method. The trade-off information may be derived by a systematical comparison of these configurations, The proposed robust design method should be useful for hybrid power systems that require both optimality and robustness.     

An unscented particle filter for ground maneuvering target tracking

In this study, an unscented particle filtering method based on an interacting multiple model (IMM) frame for a Markovian switching system is presented. The method integrates the multiple model (MM) filter with an unscented particle filter (UPF) by an interaction step at the beginning. The framework (interaction/mixing, filtering, and combination) is similar to that in a standard IMM filter, but an UPF is adopted in each model. Therefore, the filtering performance and degeneracy phenomenon of particles are improved. The filtering method addresses nonlinear and/or non-Gaussian tracking problems. Simulation results show that the method has better tracking performance compared with the standard IMM-type filter and IMM particle filter.     

Hybrid ants-like search algorithms for P2P media streaming distribution in ad hoc networks

Media streaming delivery in wireless ad hoc networks is challenging due to the stringent resource restrictions,po-tential high loss rate and the decentralized architecture. To support long and high-quality streams,one viable approach is that a media stream is partitioned into segments,and then the segments are replicated in a network and served in a peer-to-peer(P2P) fashion. However,the searching strategy for segments is one key problem with the approach. This paper proposes a hybrid ants-like search algorithm(HASA) for P2P media streaming distribution in ad hoc networks. It takes the advantages of random walks and ants-like algorithms for searching in unstructured P2P networks,such as low transmitting latency,less jitter times,and low unnecessary traffic. We quantify the performance of our scheme in terms of response time,jitter times,and network messages for media streaming distribution. Simulation results showed that it can effectively improve the search efficiency for P2P media streaming distribution in ad hoc networks.     

Reliability analysis of DOOF for Weibull distribution

INTRODUCTIONStatisticalanalysisofreliabilitytestdatashowedthatwhenthefailurenumberexceeds 2 ,therearemanytestedmethodsforprocessingthisproblem (Zhangetal.1 989) .However,inthereliabilitytestofproduct,withtheappearancesofhighreliabilityunits,evenintheaccel…     

Reliability analysis of DOOF for weibull distribution

Hierarchical Bayesian method for estimating the failure probabilityp _i under DOOF by taking the quasi-Beta distributionB(p _i−1, 1, 1,b) as the prior distribution is proposed in this paper. The weighted Least Squares Estimate method was used to obtain the formula for computing reliability distribution parameters and estimating the reliability characteristic values under DOOF. Taking one type of aerospace electrical connector as an example, the correctness of the above method through statistical analysis of electrical connector accelerated life test data was verified. Project (No. 59975081) supported by the National Natural Science Foundation of China     

从时序数据库中挖掘频繁部分周期模式的高效算法

从时序数据库中挖掘周期模式是重要的数据任务,而部分周期仅关心所有时间点中的一个子集的周期行为,它在现实世界中广泛存在．本文提出了一个新颖的基于前缀图的挖掘频繁部分周期模式的算法,并通过实验证明了该算法在执行效率上比现有的挖掘频繁部分周期模式的算法有较大提高．     

变尺度混沌优化支持向量机模型选择

1 Introduction Support vector machine (SVM) is a powerful ma-chine learning tool capable of representing non-linearrelationships and producing models that generalizeswell to unseen data .SVMhave been applied widelyinmany fields[1]such as hand-written character recogni-tion ,text categorization,computer vision,speechrec-ognition and gene classification,etc. Despite this , using an SVM requires a certainamount of model selection,i.e.,selection of the ac-tual kernel and its parameters .In rec…     

Individualization of data-segment-related parameters for improvement of EEG signal classification in brain-computer interface

In electroencephalogram (EEG) modeling techniques, data segment selection is the first and still an important step. The influence of a set of data-segment-related parameters on feature extraction and classification in an EEG-based brain-computer interface (BCI) was studied. An auto search algorithm was developed to study four datasegment-related parameters in each trial of 12 subjects’ EEG. The length of data segment (LDS), the start position of data (SPD) segment, AR order, and number of trials (NT) were used to build the model. The study showed that, compared with the classification ratio (CR) without parameter selection, the CR was increased by 20% to 30% with proper selection of these data-segment-related parameters, and the optimum parameter values were subject-dependent. This suggests that the data-segment-related parameters should be individualized when building models for BCI.     

纵向数据半参数回归模型的渐近性质

考虑纵向数据半参数回归模型:Y=Xβ g(T) ε,采用二阶段估计方法给出了参数分量β和非参数分量g(t)的估计量^βN和^gN(t),并在适当条件下研究了这些估计量的渐近正态性.     

基于原型图循环提升的高效QC-LDPC码构造和编码(英文)

通过原型图的循环提升可方便地构造准循环低密度奇偶校验(QC-LDPC)码.为了保证QC-LDPC码的性能,消除Tanner图中的短环,首先设计一种算法用于找出原型图中的有害短环,然后提出一种贪婪算法用于对提升后的校验矩阵中的单位循环位移子阵分配适合的循环位移量.与已有的DES算法相比,所提出的贪婪算法在分配循环位移量时施加了更多的限制条件来提升性能,仿真结果表明它比DES算法能消除更多的短环.当提升因子为2的整数次幂时,证明了所得QC-LDPC码的校验阵可转化成分块下三角阵的形式.利用该性质,由原型图循环提升得到的QC-LDPC码仅需对基矩阵做预处理就可以实现编码,极大地降低了QC-LDPC码的编码复杂度.