共查询到18条相似文献，搜索用时 250 毫秒
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提出了一种降低峰均功率比(PAPR)的新的融合方法,利用在发射端使经过部分传输序列(PTS)算法处理的OFDM信号再通过一种新颖的限幅滤波装置来降低PAPR. 相似文献
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EM算法是近些年来常用的求解缺失数据时的迭代算法,EM算法优点是简单易行性与普遍适用性.如果最大化不能用解析的方法实现而采用一种迭代优化的方法实现M步将产生嵌套循环计算,由此增加了计算的复杂度.基于此提出了EM梯度算法.在DS-CDMA系统中应用EM梯度算法进行检测,对比EM算法下的误码性能与收敛性能,实验结果显示EM梯度算法比标准EM算法具有相同的收敛速度. 相似文献
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空域复用多输入多输出(MIMO)系统的接收算法主要有线性接收算法(如ZF算法和MMSE算法)和非线性算法(如ML算法)两大类。其中,线性接收算法复杂性低,需要的计算量少,但是性能较差;ML算法性能较好,但是复杂度高,计算量大。因此需要寻找一种在复杂度和性能之间达到平衡的接收算法。球译码算法作为一种次优的ML算法可以较好的实现复杂度和性能间的平衡,是近年来多输入多输出(MIMO)系统译码算法中的研究热点。介绍了球译码算法的基本原理。 相似文献
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针对TDCS系统中基函数峰均比过大的问题,分析变换域通信系统影响已调信号PAPR的因素;引用正交频分复用系统中PAPR抑制的技术思路,提出了适用于TDCS系统的基于限幅法的PAPR抑制算法,并论证了该算法的有效性。理论分析和仿真结果表明:基于限幅法的TDCS中PAPR抑制算法具有较好的抑制性能,对系统误码率影响不大。 相似文献
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CCSDS图像数据压缩(IDC)标准和分组密码算法SMS4通过将数据压缩与安全分别最优化,使编译码总体性能达到最佳.该算法计算复杂度高,难以保障图像数据在资源受限网络中有效和安全传输.本文使用SMS4分组密钥对图像直流系数进行随机算术编码;对交流系数采用序列加密编码,提出一种基于CCSDS IDC的联合信源与安全编译码算法.仿真实验表明,该算法降低了计算复杂度,同时提供了良好的安全性能. 相似文献
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提出了一种基于迭代自适应机制的改进算法,有效地缩减了分层置信传播算法(HBP)的计算时间.传统HBP计算时间随指定的迭代上限增加而线性增长.为此引入消息收敛的条件判断,在迭代上限相同情况下,减少算法的迭代次数,缩减整体迭代时间.实验表明,与传统HBP相比,该方法计算时间缩减了38％以上,计算时间对整体迭代上限不敏感.该方法可以应用于使用HBP算法的其他方法. 相似文献
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Mohammad Shams Esfand Abadi Sima Kadkhodazadeh 《Journal of The Franklin Institute》2011,348(2):212-238
In this paper, the concept of proportionate adaptation is extended to the normalized subband adaptive filter (NSAF), and seven proportionate normalized subband adaptive filter algorithms are established. The proposed algorithms are proportionate normalized subband adaptive filter (PNSAF), μ‐law PNSAF (MPNSAF), improved PNSAF (IPNSAF), the improved IPNSAF (IIPNSAF), the set-membership IPNSAF (SM-IPNSAF), the selective partial update IPNSAF (SPU-IPNSAF), and SM-SPU-IPNSAF which are suitable for sparse system identification in network echo cancellation. When the impulse response of the echo path is sparse, the PNSAF has initial faster convergence than NSAF but slows down dramatically after initial convergence. The MPNSAF algorithm has fast convergence speed during the whole adaptation. The IPNSAF algorithm is suitable for both sparse and dispersive impulse responses. The SM-IPNSAF exhibits good performance with significant reduction in the overall computational complexity compared with the ordinary IPNSAF. In SPU-IPNSAF, the filter coefficients are partially updated rather than the entire filter at every adaptation. In SM-SPU-IPNSAF algorithm, the concepts of SM and SPU are combined which leads to a reduction in computational complexity. The simulation results show good performance of the proposed algorithms. 相似文献
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In this paper, we propose an adapt-then-combine (ATC) diffusion normalized Huber adaptive filtering (ATC-DNHuber) algorithm for distributed estimation in impulsive interference environments. Firstly, a normalized Huber adaptive filter (NHuber) is developed to reduce the effect of the eigenvalue spread of the input signal. Then we extend the NHuber to develop an ATC diffusion algorithm by applying the NHuber algorithm at all agents. In addition, the mean stability performance and computational complexity are analyzed theoretically. In addition, Furthermore, simulation results demonstrate that the ATC-DNHuber algorithm can perform better in identifying the unknown coefficients under the complex and changeable impulsive interference environments. 相似文献
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《Journal of The Franklin Institute》2022,359(9):4468-4488
The conjugate gradient (CG) method exhibits fast convergence speed than the steepest descent, which has received considerable attention. In this work, we propose two CG-based methods for nonlinear active noise control (NLANC). The proposed filtered-s Bessel CG (FsBCG)-I algorithm implements the functional link artificial neural network (FLANN) as a controller, and it is derived from the Matérn kernel to achieve enhanced performance in various environments. On the basis of the FsBCG-I algorithm, we further develop the FsBCG-II algorithm, which utilizes the Bessel function of the first kind to constrain outliers. As an alternative, the FsBCG-II algorithm has reduced computational complexity and similar performance as compared to the FsBCG-I algorithm. Moreover, the convergence property of the algorithms is analyzed. The proposed algorithms are compared with some highly cited previous works. Extensive simulation results demonstrate that the proposed algorithms can achieve robust performance when the noise source is impulsive, Gaussian, logistic, and time-varying. 相似文献
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《Journal of The Franklin Institute》2022,359(17):10172-10205
Recently, the sparsity-aware sign subband adaptive filter algorithm with individual-weighting-factors (S-IWF-SSAF) was devised. To accomplish performance enhancement, the variable parameter S-IWF-SSAF (VP-S-IWF-SSAF) algorithm was developed through optimizing the step-size and penalty factor, respectively. Different from the optimization scheme, we devise a family of variable step-size strategy S-IWF-SSAF (VSS-S-IWF-SSAF) algorithms based on the transient model of algorithms via minimizing the mean-square deviation (MSD) on each iteration with some reasonable and frequently adopted assumptions and Price's theorem. And in order to enhance the tracking capability, an effective reset mechanism is also incorporated into the proposed algorithms. It is worth mentioning that the presented algorithms could acquire lower computational requirements and exhibit higher steady-state estimation accuracy obviously and acceptable tracking characteristic in comparison to the VP-S-IWF-SSAF algorithm. In addition, the stable step-size range in the mean and mean square sense and steady-state performance are concluded. And the computational requirements are exhibited as well. Monte-Carlo simulations for system identification and adaptive echo cancellation applications certify the proposed algorithms acquire superior performance in contrast to other related algorithms within various system inputs under impulsive interference environments. 相似文献
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科学计算利用先进的计算能力认识和解决复杂的科学工程问题,它融建模、算法、软件研制和计算模拟为一体,是计算机实现其在高科技领域应用的必不可少的纽带和工具。计算、理论和实验一起已成为当今世界科学技术创新的主要方式。本文简要回顾了计算数学和科学计算的发展历史,从数值代数、数值逼近、最优化方法和微分方程计算方法等4个方面简要介绍了计算数学的主要研究内容和最新进展,最后提出进一步发展我国科学计算的建议。 相似文献
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《Information processing & management》2023,60(2):103205
Personalized recommender systems have been extensively studied in human-centered intelligent systems. Existing recommendation techniques have achieved comparable performance in predictive accuracy; however, the trade-off between recommendation accuracy and diversity poses new challenges, as diversification may lead to accuracy loss, whereas it can solve the over-fitting problem and enhance the user experience. In this study, we propose a heuristic optimization-based recommendation model that jointly optimizes accuracy and diversity performance by obtaining a set of optimized solutions. To establish the best accuracy-diversity balance, a novel trajectory-reinforcement-based bacterial colony optimization algorithm was developed. The improved bacterial colony optimization algorithm was comprehensively evaluated by comparing it with eight popular and state-of-the-art algorithms on ten benchmark testing problems with different degrees of complexity. Furthermore, an optimization-based recommendation model was applied to a real-world recommendation dataset. The results demonstrate that the improved bacterial colony optimization algorithm achieves the best overall performance for benchmark problems in terms of convergence and diversity. In the real-world recommendation task, the proposed approach improved the diversity performance by 1.62% to 8.62% while maintaining superior (1.88% to 40.32%) accuracy performance. Additionally, the proposed personalized recommendation model can provide a set of nondominated solutions instead of a single solution to accommodate the ever-changing preferences of users and service providers. Therefore, this work demonstrates the excellence of an optimization-based recommendation approach for solving the accuracy-diversity trade-off. 相似文献