亚临界角下的急流冲击波快速收敛计算方法

在 Ippen冲击波理论的基础上 ,给出了一个冲击波附体的亚临界角条件。为了克服图解法 ,简化式法和尝试法的不足 ,针对亚临界角条件下的急流冲击波 ,给出了一种快速迭代计算方法 ,本文证明了计算方法的收敛性 ,并分析指出方法的收敛速度至少是二阶的。由于该迭代计算方法具有计算简便 ,收敛速度快的特点 ,故不仅适合于编程计算 。

Fast method for spreading sequence estimation of DSSS signal based on maximum likelihood function

To estimate the spreading sequence of the direct sequence spread spectrum (DSSS) signal, a fast algorithm based on maximum likelihood function is proposed, and the theoretical derivation of the algorithm is provided. By simplifying the objective function of maximum likelihood estimation, the algorithm can realize sequence synchronization and sequence estimation via adaptive iteration and sliding window. Since it avoids the correlation matrix computation, the algorithm significantly reduces the storage requirement and the computation complexity. Simulations show that it is a fast convergent algorithm, and can perform well in low signal to noise ratio (SNR).

Global optimization by small-world optimization algorithm based on social relationship network

A fast global convergence algorithm, small-world optimization (SWO), was designed to solve the global optimization problems, which was inspired from small-world theory and six degrees of separation principle in sociology. Firstly, the solution space was organized into a small-world network model based on social relationship network. Secondly, a simple search strategy was adopted to navigate into this network in order to realize the optimization. In SWO, the two operators for searching the short-range contacts and long-range contacts in small-world network were corresponding to the exploitation and exploration, which have been revealed as the common features in many intelligent algorithms. The proposed algorithm was validated via popular benchmark functions and engineering problems. And also the impacts of parameters were studied. The simulation results indicate that because of the small-world theory, it is suitable for heuristic methods to search targets efficiently in this constructed small-world network model. It is not easy for each test mail to fall into a local trap by shifting into two mapping spaces in order to accelerate the convergence speed. Compared with some classical algorithms, SWO is inherited with optimal features and outstanding in convergence speed. Thus, the algorithm can be considered as a good alternative to solve global optimization problems.

Rapid Convergence of a New Wave Iterative Algorithm Used to Model a Patch Structure

The wave iterative method is a numerical method used in the electromagnetic modeling of high frequency electronic circuits. The object of the authors＇ study is to improve the convergence speed of this method by adding a new algorithm based on filtering techniques. This method requires a maximum number of iterations, noted Nmax, to achieve the convergence to the optimal value. This number wilt be reduced in order to reduce the computing time. The remaining iterations until Nmax will be calculated by the new algorithm which ensures a rapid convergence to the optimal result.

Compression and reconstruction of speech signals based on compressed sensing

Based on the approximate sparseness of speech in wavelet basis,a compressed sensing theory is applied to compress and reconstruct speech signals.Compared with one-dimensional orthogonal wavelet transform(OWT),two-dimensional OWT combined with Dmeyer and biorthogonal wavelet is firstly proposed to raise running efficiency in speech frame processing,furthermore,the threshold is set to improve the sparseness.Then an adaptive subgradient projection method(ASPM)is adopted for speech reconstruction in compressed sensing.Meanwhile,mechanism which adaptively adjusts inflation parameter in different iterations has been designed for fast convergence.Theoretical analysis and simulation results conclude that this algorithm has fast convergence,and lower reconstruction error,and also exhibits higher robustness in different noise intensities.

地基SAR技术支持下的滑坡预警预报分析方法

滑坡预警预报是滑坡动力灾害研究工作的重点和难点问题,预警及时性和预报准确性是评估滑坡预警预报效果的两个核心关键指标。地基合成孔径雷达(synthetic aperture radar,SAR)为近距离遥感监测边坡、开展滑坡预警预报工作提供了先进的技术手段,为准确定位滑体位置、圈定滑体规模、分析判断滑坡风险及预测滑坡时间提供了丰富的数据源。基于经典边坡变形演化三阶段理论,采用具有近实时性、覆盖监测区域面变形信息的地基SAR监测数据,结合边坡监测数据周期短、密度大、面覆盖的特点,提出了基于变形速度和变形面积的双指标滑坡预警方法。此外,还针对监测数据振荡性强、趋势性弱、预报时效性差的问题,根据变形速度-时间序列曲线与边坡稳定性之间负相关的关系,提出了速度取倒数、去限值、不等周期平滑处理监测数据快速处理方法,并建立了一种边坡稳定度快速收敛的滑坡破坏时间预测模型。露天矿边坡的现场实践和应用表明所提出的预警预报方法实操性强,预测结果准确。