共查询到20条相似文献,搜索用时 78 毫秒
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磁共振图像K空间中的尖峰噪声会严重影响图像质量.该文在磁共振图像压缩感知的共轭梯度重建法的基础上,提出一种新的利用磁共振图像稀疏性进行尖峰噪声修复的方法.传统的共轭梯度重建是通过小波域迭代进行的,对于K空间的尖峰噪声的消除不是最适合.首先提出压缩感知的K空间重建算法,该算法与小波域重建等效.在此基础上,提出可以较好地修复尖峰噪声的K空间部分重建算法.即在迭代过程中,以图像的稀疏性作为约束条件,仅修改尖峰噪声所遮盖区域的数据,其他位置的数据保持不变.该算法与传统的插值算法及共轭梯度算法相比,能够更好地修复K空间尖峰噪声点,减少图像伪影,同时降低了对尖峰噪声定位准确性的要求. 相似文献
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几何突变导致的相位不连续一直是相位展开中具有挑战的问题。针对这一问题,提出基于方向与变换的快速不连续相位展开算法。在提出的算法中,利用图像的结构张量估计包裹相位图的方向,将方向图进行变换和差分计算得到的可靠的权重系数图作为加权最小二乘法的权重,并使用预处理共轭梯度法迭代求解。该算法可以快速地找出不连续位置,并在不连续分割后的区域进行单独的相位展开,具有很好的识别和展开效果。详细地描述了算法的原理和实现步骤,并对算法进行仿真和实验数据验证。实验结果表明:其相位展开的均方根误差为0.36,证明该算法能够快速、准确地对不连续的包裹相位进行展开。 相似文献
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Similar to the classical meet-in-the-middle algorithm, the storage and computation complexity are the key factors that decide the efficiency of the quantum meet-in-the-middle algorithm. Aiming at the target vector of fixed weight, based on the quantum meet-in-the-middle algorithm, the algorithm for searching all n-product vectors with the same weight is presented, whose complexity is better than the exhaustive search algorithm. And the algorithm can reduce the storage complexity of the quantum meet-in-the-middle search algorithm. Then based on the algorithm and the knapsack vector of the Chor-Rivest public-key crypto of fixed weight d, we present a general quantum meet-in-the-middle search algorithm based on the target solution of fixed weight, whose computational complexity is ∑jd=(0(√Cn-k+1d-j)+O(CkjlogCkj)) with ∑i=0dCki memory cost. And the optimal value of k is given. Compared to the quantum meet-in-the-middle search algorithm for knapsack problem and the quantum algorithm for searching a target solution of fixed weight, the computational complexity of the algorithm is lower. And its storage complexity is smaller than the quantum meet-in-the-middle-algorithm. 相似文献
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Detecting community structure using label propagation with consensus weight in complex network 下载免费PDF全文
Community detection is a fundamental work to analyse the structural and functional properties of complex networks.The label propagation algorithm(LPA) is a near linear time algorithm to find a good community structure. Despite various ubsequent advances, an important issue of this algorithm has not yet been properly addressed. Random update orders within the algorithm severely hamper the stability of the identified community structure. In this paper, we executed the asic label propagation algorithm on networks multiple times, to obtain a set of consensus partitions. Based on these onsensus partitions, we created a consensus weighted graph. In this consensus weighted graph, the weight value of the dge was the proportion value that the number of node pairs allocated in the same cluster was divided by the total number f partitions. Then, we introduced consensus weight to indicate the direction of label propagation. In label update steps,y computing the mixing value of consensus weight and label frequency, a node adopted the label which has the maximum mixing value instead of the most frequent one. For extending to different networks, we introduced a proportion parameter o adjust the proportion of consensus weight and label frequency in computing mixing value. Finally, we proposed an pproach named the label propagation algorithm with consensus weight(LPAcw), and the experimental results showed that he LPAcw could enhance considerably both the stability and the accuracy of community partitions. 相似文献
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基于节能的绿色光网络路由算法的研究 总被引:1,自引:0,他引:1
在传统的网络路由算法中,一般采用最短路径算法进行路由选路,最短路径算法以节点间的距离为权重,计算一条由源节点至目的节点的权重最小的路径以完成路由。最短路径算法虽然最小化了距离长度代价,却没有考虑能耗问题,所以使用最短路径算法所得出路径的能耗并不一定是最小的。针对这一问题,提出一种新型的综合性绿色路由算法,设定能耗作为节点间的权重,融合光旁路及业务量疏导,同时考虑路由和波长分配(RWA)问题,将完成每个业务所需要的能耗最小化,实现节能。仿真结果表明,与最短路径算法相比,绿色路由算法在较大规模网络中能够节省约40%的能耗,节能效果相当显著。 相似文献
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针对粒子算法存在的问题,提出了辅助粒子算法.该算法在重采样算法基础上,引进辅助变量,对粒子的权2次计算,可使粒子权值比重采样的粒子权值变化更稳定,最后给出了红外目标模型和均方根误差函数.仿真结果表明该算法对运动目标跟踪的均值和方差上均优于标准粒子滤波、重采样粒子滤波,且提高了计算效率. 相似文献
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作为遥感研究的关键技术,遥感影像分类一直是遥感研究热点;针对目前采用BP神经网络模型进行遥感影像分类时存在的对初始权阈值敏感、易陷入局部极值和收敛速度慢的问题,为了提高BP模型遥感影像分类精度,将自适应遗传算法引入到BP网络模型参数选择中;首先运用自适应遗传算法对BP模型权阈值参数进行初始寻优,再用改进BP算法对优化的网络模型权阈值进一步精确优化,随后建立基于自适应遗传算法的BP网络分类模型,并将其应用到遥感影像数据分类研究中;仿真结果表明,新模型有效提高了遥感影像分类准确性,为遥感影像分类提出了一种新的方法,具有广泛研究价值。 相似文献
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Information filtering via weighted heat conduction algorithm 总被引:3,自引:0,他引:3
In this paper, by taking into account effects of the user and object correlations on a heat conduction (HC) algorithm, a weighted heat conduction (WHC) algorithm is presented. We argue that the edge weight of the user-object bipartite network should be embedded into the HC algorithm to measure the object similarity. The numerical results indicate that both the accuracy and diversity could be improved greatly compared with the standard HC algorithm and the optimal values reached simultaneously. On the Movielens and Netflix datasets, the algorithmic accuracy, measured by the average ranking score, can be improved by 39.7% and 56.1% in the optimal case, respectively, and the diversity could reach 0.9587 and 0.9317 when the recommendation list equals to 5. Further statistical analysis indicates that, in the optimal case, the distributions of the edge weight are changed to the Poisson form, which may be the reason why HC algorithm performance could be improved. This work highlights the effect of edge weight on a personalized recommendation study, which maybe an important factor affecting personalized recommendation performance. 相似文献
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基于驰豫超前变换中的超前展开、求和近似和延时近似技术,提出了流水线并行自适应CMA盲均衡算法。利用基于迭代短卷积的并行FIR滤波算法分析了提出的并行自适应盲均衡算法的滤波部分的高效实现结构;再利用基于组合短卷积的并行自适应系数更新算法分析了提出的并行均衡算法的系数更新部分的高效实现结构,从而得到了基于短卷积的流水线并行自适应盲均衡的完整实现框图,并分析了各模块的流水线延时需满足的关系。最后对该并行自适应盲均衡算法进行了FPGA量化实现,并通过MATLAB仿真及实际FPGA实现结果的对比,验证了本并行均衡算法的正确性和有效性。 相似文献
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加权量子搜索算法及其相位匹配条件研究 总被引:1,自引:1,他引:0
目前的Grover算法在无序数据库中搜索多个目标时,得到不同目标的几率是相等的,不考虑各个目标重要程度的差异;并且当目标数超过数据库记录总数的四分之一时,搜索到目标的几率迅速下降,当目标数超过记录总数的一半时,算法失效.针对这两个问题,首先提出一种基于加权目标的搜索算法.根据各子目标的重要程度,为每个子目标赋予一个权系数,应用这些权系数将多个子目标表示成一个量子叠加态,这样可使得到每个子目标的几率等于其自身的权系数;其次,提出自适应相位匹配条件,该条件中两次相位旋转的方向相反,大小根据目标量子叠加态和系统初始状态的内积决定.当该内积大于等于((3-√5)/8)1/2时,至多只需两步搜索,即可以恒等于1的几率得到搜索目标.实验表明,算法及其相位匹配条件是有效的. 相似文献