An improved parallel weighted bit-flipping（PWBF） algorithm is presented. To accelerate the information exchanges between check nodes and variable nodes, the bit-flipping step and the check node updating step of the ...An improved parallel weighted bit-flipping（PWBF） algorithm is presented. To accelerate the information exchanges between check nodes and variable nodes, the bit-flipping step and the check node updating step of the original algorithm are parallelized. The simulation experiments demonstrate that the improved PWBF algorithm provides about 0. 1 to 0. 3 dB coding gain over the original PWBF algorithm. And the improved algorithm achieves a higher convergence rate. The choice of the threshold is also discussed, which is used to determine whether a bit should be flipped during each iteration. The appropriate threshold can ensure that most error bits be flipped, and keep the right ones untouched at the same time. The improvement is particularly effective for decoding quasi-cyclic low-density paritycheck（QC-LDPC） codes.展开更多
A new method for power quality (PQ) disturbances identification is brought forward based on combining a neural network with least square (LS) weighted fusion algorithm. The characteristic components of PQ disturbances...A new method for power quality (PQ) disturbances identification is brought forward based on combining a neural network with least square (LS) weighted fusion algorithm. The characteristic components of PQ disturbances are distilled through an improved phase-located loop (PLL) system at first, and then five child BP ANNs with different structures are trained and adopted to identify the PQ disturbances respectively. The combining neural network fuses the identification results of these child ANNs with LS weighted fusion algorithm, and identifies PQ disturbances with the fused result finally. Compared with a single neural network, the combining one with LS weighted fusion algorithm can identify the PQ disturbances correctly when noise is strong. However, a single neural network may fail in this case. Furthermore, the combining neural network is more reliable than a single neural network. The simulation results prove the conclusions above.展开更多
By analyzing the structures of circuits,a novel approach for signal probability estimation of very large-scale integration(VLSI)based on the improved weighted averaging algorithm(IWAA)is proposed.Considering the failu...By analyzing the structures of circuits,a novel approach for signal probability estimation of very large-scale integration(VLSI)based on the improved weighted averaging algorithm(IWAA)is proposed.Considering the failure probability of the gate,first,the first reconvergent fan-ins corresponding to the reconvergent fan-outs were identified to locate the important signal correlation nodes based on the principle of homologous signal convergence.Secondly,the reconvergent fan-in nodes of the multiple reconverging structure in the circuit were identified by the sensitization path to determine the interference sources to the signal probability calculation.Then,the weighted signal probability was calculated by combining the weighted average approach to correct the signal probability.Finally,the reconvergent fan-out was quantified by the mixed-calculation strategy of signal probability to reduce the impact of multiple reconvergent fan-outs on the accuracy.Simulation results on ISCAS85 benchmarks circuits show that the proposed method has approximate linear time-space consumption with the increase in the number of the gate,and its accuracy is 4.2%higher than that of the IWAA.展开更多
Recently,the fundamental problem with Hybrid Mobile Ad-hoc Net-works(H-MANETs)is tofind a suitable and secure way of balancing the load through Internet gateways.Moreover,the selection of the gateway and overload of th...Recently,the fundamental problem with Hybrid Mobile Ad-hoc Net-works(H-MANETs)is tofind a suitable and secure way of balancing the load through Internet gateways.Moreover,the selection of the gateway and overload of the network results in packet loss and Delay(DL).For optimal performance,it is important to load balance between different gateways.As a result,a stable load balancing procedure is implemented,which selects gateways based on Fuzzy Logic(FL)and increases the efficiency of the network.In this case,since gate-ways are selected based on the number of nodes,the Energy Consumption(EC)was high.This paper presents a novel Node Quality-based Clustering Algo-rithm(NQCA)based on Fuzzy-Genetic for Cluster Head and Gateway Selection(FGCHGS).This algorithm combines NQCA with the Improved Weighted Clus-tering Algorithm(IWCA).The NQCA algorithm divides the network into clusters based upon node priority,transmission range,and neighbourfidelity.In addition,the simulation results tend to evaluate the performance effectiveness of the FFFCHGS algorithm in terms of EC,packet loss rate(PLR),etc.展开更多
针对历史轨迹加噪发布干扰轨迹时数据集的冗余问题和轨迹形状相似带来的隐私泄露风险,提出轨迹数据先约简后泛化再进行差分隐私加噪的基于改进萤火虫群优化求解的干扰轨迹发布保护机制(IGSO-SDTP)。首先,基于位置显著点约简历史轨迹数据...针对历史轨迹加噪发布干扰轨迹时数据集的冗余问题和轨迹形状相似带来的隐私泄露风险,提出轨迹数据先约简后泛化再进行差分隐私加噪的基于改进萤火虫群优化求解的干扰轨迹发布保护机制(IGSO-SDTP)。首先,基于位置显著点约简历史轨迹数据集;其次,结合k⁃匿名和差分隐私对简化后的轨迹数据集分别进行泛化和加噪;最后,设计了兼顾距离误差和轨迹相似性的加权距离,并以加权距离为评价指标,基于改进萤火虫群优化(IGSO)算法求解加权距离小的干扰轨迹。在多个数据集上的实验结果表明,与RD(Differential privacy for Raw trajectory data)、SDTP(Trajectory Protection of Simplification and Differential privacy)、LIC(Linear Index Clustering algorithm)、DPKTS(Differential Privacy based on K-means Trajectory shape Similarity)相比,IGSO-SDTP方法得到的加权距离分别降低了21.94%、9.15%、14.25%、10.55%,说明所提方法发布的干扰轨迹可用性和稳定性更好。展开更多
基金The National High Technology Research and Development Program of China (863Program) ( No2009AA01Z235,2006AA01Z263)the Research Fund of the National Mobile Communications Research Laboratory of Southeast University(No2008A10)
文摘An improved parallel weighted bit-flipping（PWBF） algorithm is presented. To accelerate the information exchanges between check nodes and variable nodes, the bit-flipping step and the check node updating step of the original algorithm are parallelized. The simulation experiments demonstrate that the improved PWBF algorithm provides about 0. 1 to 0. 3 dB coding gain over the original PWBF algorithm. And the improved algorithm achieves a higher convergence rate. The choice of the threshold is also discussed, which is used to determine whether a bit should be flipped during each iteration. The appropriate threshold can ensure that most error bits be flipped, and keep the right ones untouched at the same time. The improvement is particularly effective for decoding quasi-cyclic low-density paritycheck（QC-LDPC） codes.
基金Sponsored by the Teaching and Research Award Programfor Outstanding Young Teachers in High Education Institutions of MOE China(Grant No.ZDXM03006).
文摘A new method for power quality (PQ) disturbances identification is brought forward based on combining a neural network with least square (LS) weighted fusion algorithm. The characteristic components of PQ disturbances are distilled through an improved phase-located loop (PLL) system at first, and then five child BP ANNs with different structures are trained and adopted to identify the PQ disturbances respectively. The combining neural network fuses the identification results of these child ANNs with LS weighted fusion algorithm, and identifies PQ disturbances with the fused result finally. Compared with a single neural network, the combining one with LS weighted fusion algorithm can identify the PQ disturbances correctly when noise is strong. However, a single neural network may fail in this case. Furthermore, the combining neural network is more reliable than a single neural network. The simulation results prove the conclusions above.
基金The National Natural Science Foundation of China(No.61502422)the Natural Science Foundation of Zhejiang Province(No.LY18F020028,LQ15F020006)the Natural Science Foundation of Zhejiang University of Technology(No.2014XY007)
文摘By analyzing the structures of circuits,a novel approach for signal probability estimation of very large-scale integration(VLSI)based on the improved weighted averaging algorithm(IWAA)is proposed.Considering the failure probability of the gate,first,the first reconvergent fan-ins corresponding to the reconvergent fan-outs were identified to locate the important signal correlation nodes based on the principle of homologous signal convergence.Secondly,the reconvergent fan-in nodes of the multiple reconverging structure in the circuit were identified by the sensitization path to determine the interference sources to the signal probability calculation.Then,the weighted signal probability was calculated by combining the weighted average approach to correct the signal probability.Finally,the reconvergent fan-out was quantified by the mixed-calculation strategy of signal probability to reduce the impact of multiple reconvergent fan-outs on the accuracy.Simulation results on ISCAS85 benchmarks circuits show that the proposed method has approximate linear time-space consumption with the increase in the number of the gate,and its accuracy is 4.2%higher than that of the IWAA.
文摘Recently,the fundamental problem with Hybrid Mobile Ad-hoc Net-works(H-MANETs)is tofind a suitable and secure way of balancing the load through Internet gateways.Moreover,the selection of the gateway and overload of the network results in packet loss and Delay(DL).For optimal performance,it is important to load balance between different gateways.As a result,a stable load balancing procedure is implemented,which selects gateways based on Fuzzy Logic(FL)and increases the efficiency of the network.In this case,since gate-ways are selected based on the number of nodes,the Energy Consumption(EC)was high.This paper presents a novel Node Quality-based Clustering Algo-rithm(NQCA)based on Fuzzy-Genetic for Cluster Head and Gateway Selection(FGCHGS).This algorithm combines NQCA with the Improved Weighted Clus-tering Algorithm(IWCA).The NQCA algorithm divides the network into clusters based upon node priority,transmission range,and neighbourfidelity.In addition,the simulation results tend to evaluate the performance effectiveness of the FFFCHGS algorithm in terms of EC,packet loss rate(PLR),etc.
文摘针对历史轨迹加噪发布干扰轨迹时数据集的冗余问题和轨迹形状相似带来的隐私泄露风险,提出轨迹数据先约简后泛化再进行差分隐私加噪的基于改进萤火虫群优化求解的干扰轨迹发布保护机制(IGSO-SDTP)。首先,基于位置显著点约简历史轨迹数据集;其次,结合k⁃匿名和差分隐私对简化后的轨迹数据集分别进行泛化和加噪;最后,设计了兼顾距离误差和轨迹相似性的加权距离,并以加权距离为评价指标,基于改进萤火虫群优化(IGSO)算法求解加权距离小的干扰轨迹。在多个数据集上的实验结果表明,与RD(Differential privacy for Raw trajectory data)、SDTP(Trajectory Protection of Simplification and Differential privacy)、LIC(Linear Index Clustering algorithm)、DPKTS(Differential Privacy based on K-means Trajectory shape Similarity)相比,IGSO-SDTP方法得到的加权距离分别降低了21.94%、9.15%、14.25%、10.55%,说明所提方法发布的干扰轨迹可用性和稳定性更好。
