采用小波进行频带分割的脉冲压缩方法

针对因频带分割滤波器的不理想产生的频谱混叠、幅度以及相位失真导致子带脉压误差较大的问题,提出了一种采用小波设计的正交镜像滤波器组进行频带分割的子带脉压方法。借助小波及多分辨分析理论,利用最优频域准则设计频带分割滤波器组,消除或减小混叠失真、幅度及相位失真后,对信号进行频域分解,实现子带脉冲压缩。仿真结果表明,和传统的子带脉压方法相比,所提的脉压方法在主副瓣比方面提高了约12 dB,最大脉压误差减小了约7 dB,验证了该算法的正确性和有效性。     

经济转型期我国区域分工演化分析

本文在探讨区域分工理论的基础上,分析了经济转型时期我国区域分工的特征与发展势态。作者指出,在全国产业结构趋同客观存在的同时,资源型区域产业虚髙度化明显,区域分工向不利于其长期战略的方向发展,进而提出了协调我国区域分工的几点设想。     

中国人力资源管理的发展变革趋势

中国改革开放最大的成功在于人性的解放,中国经济社会持续快速健康发展的根本动力是人力资源开发管理所释放出来的巨大能量。本文从八个方面探讨了中国人力资源管理的发展变革趋势,以及这些变革对中国社会和企业发展带来的变化和影响。     

基于微分演化算法的DCT脆弱水印优化

基于离散余弦变换的水印嵌入技术存在变换过程中浮点数-整数转换而引入的舍入误差问题。文章采用微分演化算法修正了这类舍入误差,提高了基于离散余弦变换的脆弱数字水印的性能。同时,对该算法进行了介绍和描述,比较了它的性能。最后,就提取出来的水印的标准互相关相似度、加入水印后的影像的峰值信噪比,以及算法结果的质量和收敛率作了详细的比较。     

感应电动机伺服驱动系统自适应控制系统研究

本文针对性的提出了基于递归型小波神经网络的自适应控制性能的方案,该算法计算量减少,简化了控制结构,它可随着伺服驱动系统的运行情况的改变控制系统的结构参数,提高了伺服驱动系统对参数变化的性能,同时,也较好地改善了伺服驱动控制系统的稳态性能。通过仿真的结果验证了该控制系统方案的有效性和可行性。     

数字图像融合综述

本文对数字图像融合的主要研究内容和方向做了一个简单综述,并介绍了几种典型的数字图像融合理论与方法。     

基于小波-BP神经网络的风电场短期风速预测

对风电场风速进行较准确预测可以调整调度计划,有效减轻风电对整个电网的不利影响。文章将小波技术和神经网络相结合对风速进行短期预测。先对原始风速数据进行小波分解,再针对各小波分量分别建立BP神经网络模型进行预测,最后通过小波重构得到原始风速预测值。仿真结果表明,所提方法能够有效地提高风速预测精度。     

Oil prices and economic activity: evidence for G-7 economies based on a wavelet approach

This study examines the relationship between oil prices and economic activity in the G-7 economies during the period 1960M1–2014M07 using a wavelet approach. The results show significant differences in the relationship between these two variables depending on the frequencies. Furthermore, we find that oil price shocks affect economic activity at low frequencies (long run) in all G-7 countries, while the effect at high frequencies (short run) is limited to a few countries.     

Wagner’s law versus displacement effect

The public sector has grown dramatically over the past few centuries in many developed countries. In this article, we use wavelet methods to distinguish between two leading explanations for this growth – Wagner’s law and the displacement effect. In doing so, we use the long-term data of 10 OECD countries for a maximum time span of 1800–2009. We find that the validity of Wagner’s law is likely to vary strongly over time for each country. A roughly similar feature in most of the countries is that the law is less valid in the earliest stage of economic development as well as in the advanced stages, with the validity tending to follow an inverted U-shaped pattern with economic development. Further, our results indicate that the long-run growth of government size cannot be adequately explained by Wagner’s law. On the other hand, the displacement effect appears to account for the bulk of the growth in most of the countries.     

Are exchange rates interdependent? Evidence using wavelet analysis

We examine the co-movement in daily returns of USD–INR, EUR–INR, GBP–INR, and JPY–INR currency pair futures contracts traded on the National Stock Exchange of India (NSE) using the wavelet cohesion approach. This study contributes to the literature by examining the scantly studied area of co-movement in exchange rates and using the wavelet approach, which allows us to analyse time–frequency-wise co-movement of the time series. The empirical results indicate that the currency futures markets are nearly perfectly integrated in the long run (monthly, quarterly and biannual scales) offering little potential gains from international portfolio diversification. The discrepancies between currency futures markets are small and almost fade away within 3–6 months. Moreover, international currency diversification might offer relatively higher potential gains at intraweek, weekly, and fortnightly time horizons owing to lower correlations among the currencies under consideration. Finally, our multiple-wavelet correlation and cross-correlation analysis shows that GBP acts as a potential leader/follower across scales. The results of our analysis indicate the dynamic pattern of co-movement among the major currency futures contracts, which provides several implications for portfolio managers and international investors participating in the Indian market.