The progressive edge-growth(PEG)al-gorithm is a general method to construct short low-density parity-check(LDPC)codes and it is a greedy method to place each edge with large girths.In order to improve the performance ...The progressive edge-growth(PEG)al-gorithm is a general method to construct short low-density parity-check(LDPC)codes and it is a greedy method to place each edge with large girths.In order to improve the performance of LDPC codes,many im-proved PEG(IPEG)algorithms employ multi metrics to select surviving edges in turn.In this paper,the pro-posed edges metric(EM)based on message-passing algorithm(MPA)is introduced to PEG algorithm and the proposed EM constrained PEG(EM-PEG)algo-rithm mainly considers the independence of message passing from different nodes in Tanner graph.The numerical results show that our EM-PEG algorithm brings better bit error rate(BER)performance gains to LDPC codes than the traditional PEG algorithm and the powerful multi-edge multi-metric constrained PEG algorithm(MM-PEGA)proposed recently.In ad-dition,the multi-edge EM constrained PEG(M-EM-PEG)algorithm which adopts multi-edge EM may fur-ther improve the BER performance.展开更多
针对工业装配任务,尤其是不规则轴孔工件装配中,基于学习的前期样本质量低、训练过程不稳定等问题,提出一种融合引斥力模型(Attraction-Repulsion Model,ARM)引导机制和长短期记忆网络(Long Short Term Memory,LSTM)的柔性演员-评论家(S...针对工业装配任务,尤其是不规则轴孔工件装配中,基于学习的前期样本质量低、训练过程不稳定等问题,提出一种融合引斥力模型(Attraction-Repulsion Model,ARM)引导机制和长短期记忆网络(Long Short Term Memory,LSTM)的柔性演员-评论家(Soft Actor-Critic,SAC)算法。首先,为解决训练初期探索效率低的问题,提出一种基于引斥力模型的策略引导机制,通过目标位置信息引导机械臂运动,加速收敛过程;其次,基于长短期记忆网络对算法的策略网络和价值网络进行改进,有效利用历史信息,增强策略学习能力,提高算法的收敛速度和稳定性。仿真结果表明,所提出的算法在行星减速器中心轴装配任务中取得显著的效果,装配成功率高达99.4%,与普通SAC算法相比,平均最大接触力和力矩分别降低了68.8%和79.2%。在物理环境中装配成功率达95%以上,最大接触力和力矩分别小于10 N和1.5 N·m,验证了算法的有效性。展开更多
通过分析LDPC(Low Density Parity Check)码树图、PEG(Progressive Edge-Growth)算法和准循环LDPC码的特点,提出了一种将PEG算法和准循环矩阵相结合来构造LDPC码校验矩阵的新算法.在该算法中,首先利用PEG算法构造基矩阵,再用文中提出的...通过分析LDPC(Low Density Parity Check)码树图、PEG(Progressive Edge-Growth)算法和准循环LDPC码的特点,提出了一种将PEG算法和准循环矩阵相结合来构造LDPC码校验矩阵的新算法.在该算法中,首先利用PEG算法构造基矩阵,再用文中提出的移位参数公式和准循环LDPC码结构特点来构造循环置换矩阵;然后利用循环置换矩阵和全零矩阵对基矩阵进行扩展,从而得到围长至少为8的准循环LDPC码校验矩阵.该算法综合了PEG算法和准循环码的优点,纠错性能总体上好于PEG算法,在相同的码参数条件下的硬件实现比PEG算法简单,且参数选择具有较大灵活性.展开更多
Abstract： The layered decoding algorithm has been widely used in the implementation of Low Density Parity Check （LDPC） decoders, due to its high convergence speed. However, the pipeline operation of the layered dec...Abstract： The layered decoding algorithm has been widely used in the implementation of Low Density Parity Check （LDPC） decoders, due to its high convergence speed. However, the pipeline operation of the layered decoder may introduce memory access conflicts, which heavily deteriorates the decoder throughput. To essentially deal with the issue of memory access conflicts,展开更多
为了避免交织器产生的时延,通过改进的渐进边增长(PEG)算法和循环中国剩余定理构造了一种不规则重复累积(IRA)码。与常规的IRA码相比,提出的码字具有半随机半结构化形式,不需要设计交织器,且码长选择更加灵活。仿真结果显示,在码率为1/...为了避免交织器产生的时延,通过改进的渐进边增长(PEG)算法和循环中国剩余定理构造了一种不规则重复累积(IRA)码。与常规的IRA码相比,提出的码字具有半随机半结构化形式,不需要设计交织器,且码长选择更加灵活。仿真结果显示,在码率为1/2的条件下,当误码率为10-6时,构造的IRA(1 000,500)码与PEG-IRA(1 000,500)码和基于剩余类数对的IRA(1 000,500)码相比,在对应的相同条件下分别取得了0.2 d B和0.1 d B左右的净编码增益提升;且在码率为3/4时,所构造的IRA(16 200,11 880)码比相同码长和码率的DVB-S2标准LDPC码净编码增益提高了约0.1 d B左右。展开更多
文摘The progressive edge-growth(PEG)al-gorithm is a general method to construct short low-density parity-check(LDPC)codes and it is a greedy method to place each edge with large girths.In order to improve the performance of LDPC codes,many im-proved PEG(IPEG)algorithms employ multi metrics to select surviving edges in turn.In this paper,the pro-posed edges metric(EM)based on message-passing algorithm(MPA)is introduced to PEG algorithm and the proposed EM constrained PEG(EM-PEG)algo-rithm mainly considers the independence of message passing from different nodes in Tanner graph.The numerical results show that our EM-PEG algorithm brings better bit error rate(BER)performance gains to LDPC codes than the traditional PEG algorithm and the powerful multi-edge multi-metric constrained PEG algorithm(MM-PEGA)proposed recently.In ad-dition,the multi-edge EM constrained PEG(M-EM-PEG)algorithm which adopts multi-edge EM may fur-ther improve the BER performance.
文摘针对工业装配任务,尤其是不规则轴孔工件装配中,基于学习的前期样本质量低、训练过程不稳定等问题,提出一种融合引斥力模型(Attraction-Repulsion Model,ARM)引导机制和长短期记忆网络(Long Short Term Memory,LSTM)的柔性演员-评论家(Soft Actor-Critic,SAC)算法。首先,为解决训练初期探索效率低的问题,提出一种基于引斥力模型的策略引导机制,通过目标位置信息引导机械臂运动,加速收敛过程;其次,基于长短期记忆网络对算法的策略网络和价值网络进行改进,有效利用历史信息,增强策略学习能力,提高算法的收敛速度和稳定性。仿真结果表明,所提出的算法在行星减速器中心轴装配任务中取得显著的效果,装配成功率高达99.4%,与普通SAC算法相比,平均最大接触力和力矩分别降低了68.8%和79.2%。在物理环境中装配成功率达95%以上,最大接触力和力矩分别小于10 N和1.5 N·m,验证了算法的有效性。
文摘通过分析LDPC(Low Density Parity Check)码树图、PEG(Progressive Edge-Growth)算法和准循环LDPC码的特点,提出了一种将PEG算法和准循环矩阵相结合来构造LDPC码校验矩阵的新算法.在该算法中,首先利用PEG算法构造基矩阵,再用文中提出的移位参数公式和准循环LDPC码结构特点来构造循环置换矩阵;然后利用循环置换矩阵和全零矩阵对基矩阵进行扩展,从而得到围长至少为8的准循环LDPC码校验矩阵.该算法综合了PEG算法和准循环码的优点,纠错性能总体上好于PEG算法,在相同的码参数条件下的硬件实现比PEG算法简单,且参数选择具有较大灵活性.
基金the National Natural Science Foundation of China，the National Key Basic Research Program of China，The authors would like to thank all project partners for their valuable contributions and feedbacks
文摘Abstract： The layered decoding algorithm has been widely used in the implementation of Low Density Parity Check （LDPC） decoders, due to its high convergence speed. However, the pipeline operation of the layered decoder may introduce memory access conflicts, which heavily deteriorates the decoder throughput. To essentially deal with the issue of memory access conflicts,
文摘为了避免交织器产生的时延,通过改进的渐进边增长(PEG)算法和循环中国剩余定理构造了一种不规则重复累积(IRA)码。与常规的IRA码相比,提出的码字具有半随机半结构化形式,不需要设计交织器,且码长选择更加灵活。仿真结果显示,在码率为1/2的条件下,当误码率为10-6时,构造的IRA(1 000,500)码与PEG-IRA(1 000,500)码和基于剩余类数对的IRA(1 000,500)码相比,在对应的相同条件下分别取得了0.2 d B和0.1 d B左右的净编码增益提升;且在码率为3/4时,所构造的IRA(16 200,11 880)码比相同码长和码率的DVB-S2标准LDPC码净编码增益提高了约0.1 d B左右。
