机载雷达脉冲多普勒波束锐化技术探讨

多普勒波束锐化（ＤＢＳ）应用于机载雷达，有利于在空／地工作模式中提高主波束照射区内地面目标的方位分辨力，给主波束扫描照射区内的清晰图象。本文论述了ＤＢＳ技术的原理，并提出了在机载雷达应用中的若干问题。     

星载合成孔径雷达数据压缩

星载遥微波成像雷达的观测区域广阔，图像分辨清度高。所以，星载遥感微波成像雷达具有数据率高、数据量大的特点。这就对遥感数据的传输和存储提出了较高的要求。本文提出采取数据压缩方法，在不降低测绘带宽和测绘精度条件下，降低遥感雷达数据率和数据量，从而降低对数据链和星上数据存储设备的要求。本文还对遥感雷达原始数据压缩和遥感雷达图像数据压缩优缺点进行了比较，提出了采用遥感原始数据压缩的建议。最后，对遥感雷达原     

The Great Compression of the 1940s: The Public versus the Private Sector

Between 1940 and 1950 wage differentials narrowed substantially, a phenomenon that economic historians have called the “Great Compression.” This paper dis-aggregates the Great Compression into changes within and between the public and private sectors. We show that wage differentials declined in the public sector as well as in the private sector; had the public sector decline not taken place, the Great Compression would have been substantially smaller. In this regard, the experience of the 1940s stands in stark contrast with that of the past two decades, during which a relatively rigid public sector wage structure has dampened overall increases in wage inequality.     

合成孔径雷达图象低失真压缩研究

本文对合成孔径雷达图象压缩问题进行了探讨，依据合成孔径雷达图象统计特征，提出了几种适合合成孔径雷达图象压缩的自适应算法，并给出了压缩图象性能的评判准则。     

压缩格式和码率对视频质量的影响及应用研究

随着视频技术的发展,对能以最少的数据量获得最好的视觉效果的研究具有重要意义。对于视频质量而言,视频压缩格式及码率无疑是两个最重要的参数。本文通过对高清视频进行压缩,得到相同压缩格式不同码率和相同码率不同压缩格式的视频,然后分别对这两种情况下的视频质量进行主观评价值、PSNR值以及数据量的比较,分析其对视频质量的影响。最终得出结论,在视频压缩过程中,存在一个最高临界码率,使得视频质量相对最高且数据量最小。此外,还总结出各种常用视频压缩格式的适用范围。     

低速率语音编码技术

本文介绍了语音处理技术，各种基于ＤＳＰ技术的语音压缩算法和各种语音编码标准及领域，介绍了几种语音ＤＳＰ的专用芯片。     

一种波形音频文件压缩的实现

描述了波形音频文件的格式，提出了一种压缩波形音频文件的方法，给出了压缩依据和压缩结果，最终的结果表明压缩方法是可行的。     

压榨法在精油提取中的应用

压榨法也是从芳香植物原料提取精油的方法之一,主要用于制造柑橘类精油。如甜橙、柠檬、香柠檬以及白柠檬等的果皮提油均采用此法。压榨法在加工过程中不受热,因此又称为冷榨法。     

时空压缩下研发要素流动是否提升了区域绿色创新效率

基于地区高铁通勤时间构建空间权重矩阵,采用空间杜宾模型（SDM）和面板门槛模型（PTR）实证检验时空压缩下研发要素流动对区域绿色创新效率的影响。研究发现：高铁开通后,研发要素流动对绿色创新效率的促进作用显著增强,且研发人员流动的直接效应更显著;时空压缩下研发要素流动对绿色创新效率的影响存在地区异质性,东部地区因创新资源集聚程度和能力水平较高,更易从中获益,而西部地区受限于地理位置和经济发展阶段,其研发要素流动对绿色创新效率的影响偏弱;研发人员流动、财政科技支出、基础设施建设和市场化水平4种调节因素均表现出门槛特征,且呈现出梯度式增强。     

Forecasting occupancy rate with Bayesian compression methods

The curse of dimensionality is a challenge that researchers often face when dealing with large Vector Autoregressions (VARs). Different approaches have been proposed in the literature to address this issue. In this paper, we propose a new method based on the idea of compressed regression. In particular, we introduce two novel nonlinear compressed VARs to forecast the occupancy rate of hotels that compete within a narrow geographical area. We make the models more flexible through the introduction of neural networks, and compare their performance against several competing models. The empirical results show that the new compressed VARs outperform all other models, and their accuracy is preserved across nearly all forecast horizons from 1 to 36 months.This article also launches the Annals of Tourism Research Curated Collection on Tourism Demand Forecasting, a special selection of research in this field.