A novel noise reduction technique for underwater acoustic signals based on complete ensemble empirical mode decomposition with adaptive noise,minimum mean square variance criterion and least mean square adaptive filter

Underwater acoustic signal processing is one of the research hotspots in underwater acoustics. Noise reduction of underwater acoustic signals is the key to underwater acoustic signal processing. Owing to the complexity of marine environment and the particularity of underwater acoustic channel, noise reduction of underwater acoustic signals has always been a difficult challenge in the field of underwater acoustic signal processing. In order to solve the dilemma, we proposed a novel noise reduction technique for underwater acoustic signals based on complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN), minimum mean square variance criterion (MMSVC) and least mean square adaptive filter (LMSAF). This noise reduction technique, named CEEMDAN-MMSVC-LMSAF, has three main advantages: (i) as an improved algorithm of empirical mode decomposition (EMD) and ensemble EMD (EEMD), CEEMDAN can better suppress mode mixing, and can avoid selecting the number of decomposition in variational mode decomposition (VMD); (ii) MMSVC can identify noisy intrinsic mode function (IMF), and can avoid selecting thresholds of different permutation entropies; (iii) for noise reduction of noisy IMFs, LMSAF overcomes the selection of decomposition number and basis function for wavelet noise reduction. Firstly, CEEMDAN decomposes the original signal into IMFs, which can be divided into noisy IMFs and real IMFs. Then, MMSVC and LMSAF are used to detect identify noisy IMFs and remove noise components from noisy IMFs. Finally, both denoised noisy IMFs and real IMFs are reconstructed and the final denoised signal is obtained. Compared with other noise reduction techniques, the validity of CEEMDAN-MMSVC-LMSAF can be proved by the analysis of simulation signals and real underwater acoustic signals, which has the better noise reduction effect and has practical application value. CEEMDAN-MMSVC-LMSAF also provides a reliable basis for the detection, feature extraction, classification and recognition of underwater acoustic signals.     

Pricing and capacity allocation strategies: Implications for manufacturers with product sharing

Emerging sharing modes, like the consumer-to-consumer (C2C) sharing of Uber and the business-to-consumer (B2C) sharing of GoFun, have considerably affected the retailing markets of traditional manufacturers, who are motivated to consider product sharing when making pricing and capacity decisions, particularly electric car manufacturers with limited capacity. In this paper, we examine the equilibrium pricing for a capacity-constrained manufacturer under various sharing modes and further analyze the impact of capacity constraint on the manufacturer's sharing mode selection as well as equilibrium outcomes. We find that manufacturers with low-cost products prefer B2C sharing while those with high-cost products prefer C2C sharing except when the sharing price is moderate. However, limited capacity motivates manufacturers to enter into the B2C sharing under a relatively low sharing price, and raise the total usage level by sharing high-cost products. We also show that the equilibrium capacity allocated to the sharing market with low-cost products first increases and then decreases. Finally, we find that sharing low-cost products with a high limited capacity leads to a lower retail price under B2C sharing, which creates a win-win situation for both the manufacturer and consumers. However, sharing high-cost products with a low limited capacity creates a win-lose situation for them.     

战时维修保障力量配置与保障方式确定方法研究

通过界定维修组时和保障方式的基本概念,建立了装备维修组时和保障力量可用组时预计模型,在此基础上,建立了维修保障力量和保障方式的关系模型,提出战时维修保障力量配置和保障方式确定方法,并以实例对该方法进行了说明和论证,为最优使用维修保障力量、筹划保障行动提供可借鉴的方法。     

一种基于Q-R矩阵分解的自适应滤波算法

由于计算误差等因素的影响,致使滤波协方差阵不对称或负定,从而导致滤波器发散,影响滤波算法的收敛速度和稳定性。在机动加速度"当前"统计自适应卡尔曼滤波算法的基础上,引入了基于Q-R矩阵分解的自适应卡尔曼滤波算法。将协方差阵分解为两个矩阵的乘积,来保证协方差矩阵的正定性。仿真结果表明,该算法可以较好地跟踪机动目标,具有精度高、稳定好、收敛快等特点。     

一种钢管焊接结构焊接节点损伤识别的新方法

采用端部半刚性连接梁单元模型进行模拟焊接节点的损伤,并基于应变模态理论,提出了一种焊接节点损伤识别两步法。第一步,先整体测量结构的位移模态并推导出应变模态,然后采用改进后的目标函数,通过信赖域优化算法对损伤节点位置进行准确判定;第二步,采用提出的杆端应变模态变化比指标,实现焊接节点损伤程度的精确识别。经工程实例的数值仿真及试验分析,验证了该方法的有效性及优越性,为解决这类大型焊接结构焊接节点的损伤识别问题提供了新思路。     

GPS动态定位中整周模糊度的快速解算

在导航中快速和高精度GPS定位需要解算差分载波相位的整周模糊度值.目前整周模糊度的求解方法,丢失了对提高未知参数估值精度很有用的历元信息,并且在去相关过程中必须使方差阵为正定阵,不仅解算难度大,还可能出现病态分解,使得去相关失败.提出了一种GPS整周模糊度的快速解算方法,首先利用卡尔曼算法求解整周模糊度的浮点解;其次确定搜索空间,对协方差阵进行Cholesky分解,削弱其相关性;最后用ratio检验得出最终解.通过理论推导和基于实测数据的仿真分析表明,卡尔曼算法有效地利用多历元信息提高了浮点解的精度,并且在去相关过程中解决了方差阵必须为正定阵的问题,避免出现病态分解,使得搜索空间得到明显的改善,提高了效率,具有实际的应用价值.     

基于状态评估的复杂系统任务成功性评估

给出了基于状态评估的复杂任务成功性评估模型,通过任务分解确定相关功能单元,而后利用D-S证据理论对相关功能单元的技术状态展开评估,结合具体任务剖面与技术状态评估结果实现对复杂系统的任务成功性评估。最后以实例表明该方法运用在某型装甲装备任务成功性评估上的有效性和实用性。     

并行环境下的管理信息系统开发模式研究

通过分析生命周期法、原型法等传统管理信息系统开发方法存在的一些不足之处,以及将并行工程的思想应用到管理信息系统的开发中,提出了一种基于并行环境下的管理信息系统开发模式,并结合装甲装备器材资源调度系统的开发,对这种并行环境开发模式进行了探讨和研究.     

多媒体网络辅助英语教学模式中教师的作用

随着信息技术的迅猛发展,英语教学改革出现了新的契机。多媒体和网络以其形象化的表达方式,真实的语言环境,建构了开放的教学空间,优化了外语教学环境。这必然会引起外语教学从教材、教学方法、教学手段到整个教学过程的重大变革,大学英语教学模式也将随之发生深刻变化。如何适应这一变化,是教师应该重点考虑的问题。     

消防科学数字图书馆建设模式探析

消防科学数字图书馆建设模式研究是消防科学数字图书馆的基础性工作。从消防科学数字图书馆建设模式研究的目的意义、指导原则和研究内容出发,论述了应如何建立消防科学数字图书馆的建设模式。