Research on the Method of De-noising the Short-wave Time Signal at Low SNR

A voice enhancement algorithm based on the Empirical Mode Decomposition (EMD) and the improved spectral subtraction is proposed for the low-SNR (Signal Noise Ratio) shortwave time signal. This method is proposed to solve the problem that the shortwave time signal cannot be used for timing in complex noisy environments. The core idea of this method is to use the Hilbert-Huang Transform (HHT) algorithm to make the empirical mode decomposition on the noisy shortwave signal, and to select the intrinsic mode functions containing the shortwave signal information for the signal reconstruction by through the maximum correlation. Then, to make the spectral subtraction on the reconstructed signal to achieve the purpose of noise reduction. The experimental result shows that this method has a better noise reduction than the traditional methods.     

基于模糊神经网络(FNN)的赤潮预警预测研究

为研究各种理化因子与赤潮藻类浓度间的非线性对应规律和有效预测赤潮藻类浓度,构建了基于BP 算法的一个四层模糊神经网络模型。将模糊神经网络(FNN)技术引入赤潮预测研究,并与普通 BP 网络、RBF 网络的结果作比较,结果表明,该模型能够较好地反演出各种理化因子与夜光藻密度的非线性对应变化规律,有更好的预测功能。     

希尔伯特-黄变换的端点延拓

希尔伯特-黄变换(HHT)是近年来发展起来的一种新的时间序列信号分析方法.该文在对HHT深入研究与充分肯定的基础上,发展了信号的镜像闭合延拓和包络的极值延拓两种方法.通过几个典型的例子检验了两种方法,并与Huang等(1998,1999)进行了比较,得到了令人满意的结果.镜像闭合延拓法根据信号端点的分布特性,把镜子放在具有对称性的极值位置,通过镜像法把镜内信号映射成一个周期性的信号,不存在端点,从根本上避免了经验模态分解和希尔伯特变换的端点问题.极值延拓法简单易行,具有与镜像闭合法相当的效果,在处理非对称波形信号时更显其优越性.     

全球百年海表面温度年际和年代际变化特征分析

利用100 a(1903—2002年)HadiSST的逐月资料,将全球海表面温度异常(SSTA)作为整体进行经验正交函数分解(EOF分解),提取了控制各大洋SSTA的主导模态和各大洋之间的联合模态,分析了相应的空间分布和时间序列。研究结果表明:SSTA变化最剧烈的海区是赤道中东太平洋、西北大西洋湾流海区和北太平洋黑潮延伸体海区。热带太平洋厄尔尼诺和南方涛动是主导模态并具有2~7 a周期的年际变化;SSTA变化第二主模态和第三主模态都是以大约70 a为周期的年代际变化为主的跨大洋联合模态。第二主模态的空间分布主要表现为中纬度北太平洋和北大西洋反位相、热带太平洋与大西洋反位相的太平洋-大西洋双偶极子型分布。SSTA变化的第三模态主要呈现南北半球海洋反位相的特征,为北太平洋-北大西洋-南大洋联合模态。第四模态基本上是反映各个不同海域特有的局地海洋-大气相互作用模态,该模态的时间序列具有1~4 a周期的年际变化和约9 a周期的年代际变化。     

Comparison of long-, medium- and short-term variations of beach profiles with and without submerged geological control

Victoria Beach (Cadiz, Spain) comprises a rocky flat outcrop in its northern zone and a sand-rich southern zone. These natural features allowed for a 5-year monitoring period and subsequent analysis of two different profiles (one in each zone) based on differences in bottom contours. Topo-bathymetric data were analysed using empirical orthogonal functions (EOFs) to determine changes over the short-, medium- and long-term. Several morphologic phenomena were identified (generalised erosion, seasonal or summer–winter tilting of the profile around different hinge points, berm development and its posterior destruction, etc.) in terms of their importance in explaining the variability of the collected data for both profiles. It is worth mentioning that both profiles undergo parallel regression in the medium-term. Thus, the 1st eigenfunction enabled us to identify the true regression of the beach shoreline, independent of seasonal or summer–winter slope changes. Reconstruction of profiles using EOF components demonstrated that though accretion periods in the medium-term were similar for both types of profiles, the accretion speed was much faster in the sand-rich profile than in the reef-protected profile (1.01 m³/day versus 0.33 m³/day). Moreover, the seasonal erosion rate and the subsequent shoreline retreat for the sand-rich profile were much larger than for the reef-protected profile (121 m³/year versus 29 m³/year). Analysis in the short-term (changes induced by a single day's storm) showed an instantaneous tilting of the profile, with the mobilised sand volume being much greater for the sand-rich than for the reef-protected profile (68 m³/m versus 12 m³/m).     

Alternative Fuzzy Cluster segmentation of remote sensing images based on Adaptive Genetic Algorithm

Remote sensing image segmentation is the basis of image understanding and analysis. However, the precision and the speed of segmentation can not meet the need of image analysis, due to strong uncertainty and rich texture details of remote sensing images. We proposed a new segmentation method based on Adaptive Genetic Algorithm (AGA) and Alternative Fuzzy C-Means (AFCM). Segmentation thresholds were identified by AGA. Then the image was segmented by AFCM. The results indicate that the precision and the speed of segmentation have been greatly increased, and the accuracy of threshold selection is much higher compared with traditional Otsu and Fuzzy C-Means (FCM) segmentation methods. The segmentation results also show that multi-thresholds segmentation has been achieved by combining AGA with AFCM.     

结合遗传算法的LVQ神经网络在声学底质分类中的应用

学习向量量化（Learning Vector Quantization,LVQ）神经网络在声学底质分类中具有广泛应用. 常用的LVQ神经网络存在神经元未被充分利用以及算法对初值敏感的问题,影响底质分类精度. 本文提出采用遗传算法（Genetic Algorithms,GA）优化神经网络的初始值,将GA与LVQ神经网络结合起来,迅速得到最佳的神经网络初始权值向量,实现对海底基岩、砾石、砂、细砂以及泥等底质类型的快速、准确识别. 将其应用于青岛胶州湾海区底质分类识别研究中,通过与标准的LVQ神经网络的分类结果进行比较表明,该方法在分类速度以及精度上都有了较大提高.     

Regional evapotranspiration rate of oasis and surrounding desert

The surface energy balance algorithm for land method was used in this study to calculate the evapotranspiration (ET) rate for the middle reaches of the Heihe River Basin, Gansu Province, China, to analyse ET distribution within the oasis and the surrounding desert and, especially, on the edge zone of the oasis. Five profile graphs were created vertical to the river. Because of the inverse humidity phenomenon, the least amount of evapotranspiration occurred on the desert close to the oasis. The average evapotranspiration rate was roughly proportioned from the edge of the oasis to inside and outside its boundary. Two meteorological ground stations located close to the oasis edge showed a notable difference in net radiation flux that led to the difference found in ET. The primary reason for the significant differences observed in net radiation may be largely the result of differences in flux reflectivity and surface temperature. Meteorological data show that water supply also played an important role. Copyright © 2012 John Wiley & Sons, Ltd.     

气象场相关结构对EOFs展开稳定性的影响

本文从矩阵扰动理论出发,提出利用矩阵的范数(norm)作为度量气象场随机扰动的稳定性指标,并由此间接推估EOFs展开的稳定性。经理论论证、数值试验和实例计算表明,气象场的相关性越好,达到稳定相关结构所需样本越小,由此得到的EOFs稳定性也越好,反之则不然。上述规律又直接受样本大小n和站点数目p的影响。对于不同的气象场来说,达到稳定EOFs的样本临界值不同,必须警惕EOFs展开有可能不是稳定的。     

北半球月平均环流异常垂直结构的综合分析

本文用一种时空综合的经验正交函数分析方法,对北半球100、500和700hPa三层月平均高度距平场进行展开,得到了不仅能反映各层高度距平场本身的空间结构分布特征,而且能同时反映各层高层距平场之间有机联系的特征向量场.分析结果表明:北半球月平均环流异常在垂直方向上具有明显的相当正压性结构特征.