一类变系数高阶线性齐次微分方程解的探求(英文)

本文对系数全为多项式和广义多项式的n阶线性齐次微分方程引入特征方程的概念。给出了具有指数型解的充要条件，推广了经典的常系数线性方程和著名的Euler方程的的解法，为求解变系数线性微分方程提供了有效的方法。     

非线性热传导方程u_t-Δu=D~βf(u)的Cauchy问题的整体解及渐近性

本文利用压缩映象原理及线性方程 Cauchy 问题的解的衰减性佶计,研究了一类非线性热传导方程 Cauchy 问题的整体解的存在唯一性及渐近性,得到当初值及非线性项满足一定条件之下Cauchy 问题的适当性。从而补充了文[3]的结果,首次指出了文[1]的结果是对半线性方程独有的。     

降低线性调频脉冲压缩信号旁瓣的方法

讨论线性调频脉冲压缩信号距离旁瓣的抑制。研究如何降低小时带积线性调频信号距离旁瓣电平问题,针对该信号频谱矩形特性差,提出了采用频谱修正方法来提高脉冲压缩信号的主副比。该方法具有全数字式处理特点,适宜使用IMS A100器件实现脉冲压缩处理。计算机模拟结果表明,无论是小时带积还是大时带积的线性调频信号,经谱修正后,脉冲压缩信号的主副比均舍得到提高。     

改善全息圆锥准直线及提高准直精度的一种方法

用一张计算全息图可产生锥面波,锥面波衍射图样的中心在空间是连续的,可作为直线基准。本文提出了提高锥面波直线准直精度的一种方法即空间滤波法。实验结果与理论分析一致。     

环境分权、地方政府竞争对绿色技术创新影响的“本地—邻地”效应

随着绿色发展成为五大发展理念之一,各地政府推进绿色技术创新成为降低环境污染和提高增长质量的主要途径。为了考察地方政府环境分权和竞争对绿色技术创新影响的“本地—邻地”效应,本文利用非期望产出EBM模型测度绿色技术创新程度,并将绿色技术创新指数引入动态空间杜宾模型。最后,结合2003-2017年中国省级面板数据进行实证分析。研究发现：(1)绿色技术创新具有显著的路径依赖、空间集聚以及邻近地区的策略竞争效应;(2)环境分权对本地和邻地绿色技术创新的影响呈“U型”变动特征,且现阶段并未跨越分权驱动创新的临界点;(3)环境分权与地方政府竞争的交互效应整体为负,环境行政分权、环境监察分权和环境监测分权等不同类型环境分权采取的策略并不相同;(4)区域环境分权产生的绿色技术创新激励效应存在异质性,中西部地区环境分权对绿色技术创新的激励效果更强。     

数字经济与城市群协同发展：基于夜间灯光数据的研究

准确认识数字经济与城市群协同发展的关系,有利于拓展数字经济影响的评估视角,也为发挥数字经济和区域一体化的融合倍增效应提供有益思路。研究发现,数字经济时代城市群辐射带动区域协同发展的步伐正在加快,数据要素跨域流通打破了城市群内部和城市群之间的市场分割,助推城市群边界的有效扩大。数字经济促进城市群协同发展主要通过两个作用机制,一是推动创新主体跨城市跨区域进行合作创新,促进城市协同创新网络发育壮大;二是提升城市空间集中度,增强邻近空间范围内的城市要素集聚能力。数字经济的网络性、跳跃性及外部性特征放大了中心城市对外围城市的辐射带动作用和空间溢出效应,因此构建与数字经济相匹配的区域一体化协调机制和要素统筹配置机制正当其时。     

收费公路运营效率测度及时空分异研究

收费公路行业内部债务治理与外部减税降费均要求收费公路运营降本增效。为了探析收费公路运营效率水平及其空间分布格局,使用SBM模型测度了2014—2020年29个省份收费公路运营效率,进而采用泰尔指数和Moran's I指数分析了其时空分异特征。研究认为:收费公路运营存在着效率较低且在时间维度上没有明显增长的趋势,在空间上存在发展不平衡问题,收费公路运营效率的区域差异主要来源于区域内部差异,区域内差异的贡献率平均达到81.578%; 收费公路运营效率具有空间正相关性,呈现出显著的“高-高”集聚和“低-低”集聚的空间特征,运营效率较高的省份对相邻省份具有正向溢出效应。研究表明,各省针对相邻省份或最近省份的运营效率现状,结合自身的比较优势探索产业升级或者物流发展模式,充分发挥相邻省份的经济发展和产业集聚对本省收费公路运营的辐射带动作用,推动建立起收费公路跨区域合作运营机制。     

Approximation of density functions by orthogonal series with grouped data

Summary Letg(x) andf(x) be continuous density function on (a, b) and let {ϕ_j} be a complete orthonormal sequence of functions onL ₂(g), which is the set of squared integrable functions weighted byg on (a, b). Suppose that over (a, b). Given a grouped sample of sizen fromf(x), the paper investigates the asymptotic properties of the restricted maximum likelihood estimator of density, obtained by setting all but the firstm of the ϑ_j’s equal to0. Practical suggestions are given for performing estimation via the use of Fourier and Legendre polynomial series. Research partially supported by: CNR grant, n. 93. 00837. CT10.     

Implementing partial least squares

Partial least squares (PLS) regression has been proposed as an alternative regression technique to more traditional approaches such as principal components regression and ridge regression. A number of algorithms have appeared in the literature which have been shown to be equivalent. Someone wishing to implement PLS regression in a programming language or within a statistical package must choose which algorithm to use. We investigate the implementation of univariate PLS algorithms within FORTRAN and the Matlab (1993) and Splus (1992) environments, comparing theoretical measures of execution speed based on flop counts with their observed execution times. We also comment on the ease with which the algorithms may be implemented in the different environments. Finally, we investigate the merits of using the orthogonal invariance of PLS regression to improve the algorithms.     

Sampling from spatial databases

This paper deals with techniques for obtaining random point samples from spatial databases. We seek random points from a continuous domain (usually ²) which satisfy a spatial predicate that is represented in the database as a collection of polygons. Several applications of spatial sampling (e.g. environmental monitoring, agronomy, forestry, etc) are described. Sampling problems are characterized in terms of two key parameters: coverage (selectivity), and expected stabbing number (overlap). We discuss two fundamental approaches to sampling with spatial predicates, depending on whether we sample first or evaluate the predicate first. The approaches are described in the context of both quadtrees and R-trees, detailing the sample first, acceptance/rejection tree, and partial area tree algorithms. A sequential algorithm, the one-pass spatial reservoir algorithm is also described. The relative performance of the various sampling algorithms is compared and choice of preferred algorithms is suggested. We conclude with a short discussion of possible extensions.