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- Genre: Doctoral Dissertation
- Creators: Shen, Wei
- Member of: ASU Electronic Theses and Dissertations
Description
The theme for this work is the development of fast numerical algorithms for sparse optimization as well as their applications in medical imaging and source localization using sensor array processing. Due to the recently proposed theory of Compressive Sensing (CS), the $\ell_1$ minimization problem attracts more attention for its ability to exploit sparsity. Traditional interior point methods encounter difficulties in computation for solving the CS applications. In the first part of this work, a fast algorithm based on the augmented Lagrangian method for solving the large-scale TV-$\ell_1$ regularized inverse problem is proposed. Specifically, by taking advantage of the separable structure, the original problem can be approximated via the sum of a series of simple functions with closed form solutions. A preconditioner for solving the block Toeplitz with Toeplitz block (BTTB) linear system is proposed to accelerate the computation. An in-depth discussion on the rate of convergence and the optimal parameter selection criteria is given. Numerical experiments are used to test the performance and the robustness of the proposed algorithm to a wide range of parameter values. Applications of the algorithm in magnetic resonance (MR) imaging and a comparison with other existing methods are included. The second part of this work is the application of the TV-$\ell_1$ model in source localization using sensor arrays. The array output is reformulated into a sparse waveform via an over-complete basis and study the $\ell_p$-norm properties in detecting the sparsity. An algorithm is proposed for minimizing a non-convex problem. According to the results of numerical experiments, the proposed algorithm with the aid of the $\ell_p$-norm can resolve closely distributed sources with higher accuracy than other existing methods.
ContributorsShen, Wei (Author) / Mittlemann, Hans D (Thesis advisor) / Renaut, Rosemary A. (Committee member) / Jackiewicz, Zdzislaw (Committee member) / Gelb, Anne (Committee member) / Ringhofer, Christian (Committee member) / Arizona State University (Publisher)
Created2011
Some topics concerning the singular value decomposition and generalized singular value decomposition
Description
This dissertation involves three problems that are all related by the use of the singular value decomposition (SVD) or generalized singular value decomposition (GSVD). The specific problems are (i) derivation of a generalized singular value expansion (GSVE), (ii) analysis of the properties of the chi-squared method for regularization parameter selection in the case of nonnormal data and (iii) formulation of a partial canonical correlation concept for continuous time stochastic processes. The finite dimensional SVD has an infinite dimensional generalization to compact operators. However, the form of the finite dimensional GSVD developed in, e.g., Van Loan does not extend directly to infinite dimensions as a result of a key step in the proof that is specific to the matrix case. Thus, the first problem of interest is to find an infinite dimensional version of the GSVD. One such GSVE for compact operators on separable Hilbert spaces is developed. The second problem concerns regularization parameter estimation. The chi-squared method for nonnormal data is considered. A form of the optimized regularization criterion that pertains to measured data or signals with nonnormal noise is derived. Large sample theory for phi-mixing processes is used to derive a central limit theorem for the chi-squared criterion that holds under certain conditions. Departures from normality are seen to manifest in the need for a possibly different scale factor in normalization rather than what would be used under the assumption of normality. The consequences of our large sample work are illustrated by empirical experiments. For the third problem, a new approach is examined for studying the relationships between a collection of functional random variables. The idea is based on the work of Sunder that provides mappings to connect the elements of algebraic and orthogonal direct sums of subspaces in a Hilbert space. When combined with a key isometry associated with a particular Hilbert space indexed stochastic process, this leads to a useful formulation for situations that involve the study of several second order processes. In particular, using our approach with two processes provides an independent derivation of the functional canonical correlation analysis (CCA) results of Eubank and Hsing. For more than two processes, a rigorous derivation of the functional partial canonical correlation analysis (PCCA) concept that applies to both finite and infinite dimensional settings is obtained.
ContributorsHuang, Qing (Author) / Eubank, Randall (Thesis advisor) / Renaut, Rosemary (Thesis advisor) / Cochran, Douglas (Committee member) / Gelb, Anne (Committee member) / Young, Dennis (Committee member) / Arizona State University (Publisher)
Created2012
Description
Structural features of canonical wall-bounded turbulent flows are described using several techniques, including proper orthogonal decomposition (POD). The canonical wall-bounded turbulent flows of channels, pipes, and flat-plate boundary layers include physics important to a wide variety of practical fluid flows with a minimum of geometric complications. Yet, significant questions remain for their turbulent motions' form, organization to compose very long motions, and relationship to vortical structures. POD extracts highly energetic structures from flow fields and is one tool to further understand the turbulence physics. A variety of direct numerical simulations provide velocity fields suitable for detailed analysis. Since POD modes require significant interpretation, this study begins with wall-normal, one-dimensional POD for a set of turbulent channel flows. Important features of the modes and their scaling are interpreted in light of flow physics, also leading to a method of synthesizing one-dimensional POD modes. Properties of a pipe flow simulation are then studied via several methods. The presence of very long streamwise motions is assessed using a number of statistical quantities, including energy spectra, which are compared to experiments. Further properties of energy spectra, including their relation to fictitious forces associated with mean Reynolds stress, are considered in depth. After reviewing salient features of turbulent structures previously observed in relevant experiments, structures in the pipe flow are examined in greater detail. A variety of methods reveal organization patterns of structures in instantaneous fields and their associated vortical structures. Properties of POD modes for a boundary layer flow are considered. Finally, very wide modes that occur when computing POD modes in all three canonical flows are compared. The results demonstrate that POD extracts structures relevant to characterizing wall-bounded turbulent flows. However, significant care is necessary in interpreting POD results, for which modes can be categorized according to their self-similarity. Additional analysis techniques reveal the organization of smaller motions in characteristic patterns to compose very long motions in pipe flows. The very large scale motions are observed to contribute large fractions of turbulent kinetic energy and Reynolds stress. The associated vortical structures possess characteristics of hairpins, but are commonly distorted from pristine hairpin geometries.
ContributorsBaltzer, Jon Ronald (Author) / Adrian, Ronald J (Thesis advisor) / Calhoun, Ronald (Committee member) / Gelb, Anne (Committee member) / Herrmann, Marcus (Committee member) / Squires, Kyle D (Committee member) / Arizona State University (Publisher)
Created2012
Description
Graph coloring is about allocating resources that can be shared except where there are certain pairwise conflicts between recipients. The simplest coloring algorithm that attempts to conserve resources is called first fit. Interval graphs are used in models for scheduling (in computer science and operations research) and in biochemistry for one-dimensional molecules such as genetic material. It is not known precisely how much waste in the worst case is due to the first-fit algorithm for coloring interval graphs. However, after decades of research the range is narrow. Kierstead proved that the performance ratio R is at most 40. Pemmaraju, Raman, and Varadarajan proved that R is at most 10. This can be improved to 8. Witsenhausen, and independently Chrobak and Slusarek, proved that R is at least 4. Slusarek improved this to 4.45. Kierstead and Trotter extended the method of Chrobak and Slusarek to one good for a lower bound of 4.99999 or so. The method relies on number sequences with a certain property of order. It is shown here that each sequence considered in the construction satisfies a linear recurrence; that R is at least 5; that the Fibonacci sequence is in some sense minimally useless for the construction; and that the Fibonacci sequence is a point of accumulation in some space for the useful sequences of the construction. Limitations of all earlier constructions are revealed.
ContributorsSmith, David A. (Author) / Kierstead, Henry A. (Thesis advisor) / Czygrinow, Andrzej (Committee member) / Gelb, Anne (Committee member) / Hurlbert, Glenn H. (Committee member) / Kadell, Kevin W. J. (Committee member) / Arizona State University (Publisher)
Created2010
Description政府引导基金自诞生至今，始终处于管理模式的摸索状态。本文试图从公司治理的角度分析不同利益方（政府、社会出资人以及管理人）之间的博弈关系以及其对引导基金投资效果的影响。政府引导基金的注册数量和规模在过去十几年中得到了快速显著的发展。从引导基金设立的政府行政层级来看，地县级政府设立基金是引导基金出资中的绝对主力。本文拟深入研究地县级政府引导基金的运作模式，尝试探索其治理结构与投资效果。
目前，引导基金的运作模式仍然处于摸索阶段，论文试图对引导基金若干个指标做出客观比较，分析政府参与度对资金投资效果的影响，希望对未来引导基金的设立模式选择提供有力的理论基础。为实现较好的研究效果，论文选择了某经济发达的地级市的样本进行了研究，该市的政府引导私募股权基金发展程度相对较高，市本级以及区县级均有较多的政府引导私募股权基金，该市范围政府引导私募股权基金可研究价值相对较高。在样本选择方面，论文将采样某市及所辖区县政府直接出资基金十六只，针对其参与设立的直投基金以及直接投资项目进行分析。同时，论文还总正反两个方面选择了两个经典案例进行详细剖析。
论文发现，市场化运作程度越低，引导基金所期望实现的目标效果相对不理想，投资效果越差。政府在决策中所占比重越高，形成的投资决策对于项目成长性判断的准确度越差，对地方经济社会发展的综合贡献越低。然而，纯粹的商业运作，无法实现引导基金所承担的社会使命。对不同的资金诉求导致的投资要求在不同的决策层级实现，通过政府或其代表出资方对管理方以协议约束的方式保证其投资行为而不再进行对单个项目进行价值判断，是有效实现引导诉求和专业判断兼顾的引导基金管理模式。
论文建议，在经济相对发达地区，政府引导基金应该积极采用市场化运作模式，在现有可选择的模式中，政府引导基金以LP身份且获取咨询委角色，从外部监察约束角度对基金进行投资引导的模式为最佳选择。
ContributorsWu, Di (Author) / Pei, Ker-Wei (Thesis advisor) / Wu, Fei (Thesis advisor) / Zhu, David (Committee member) / Arizona State University (Publisher)
Created2022
Description本文对中国制药企业并购溢价影响因素进行了研究，提出了对制药企业并购非常重要的两个新的影响因素：可生产药品批文和在研新药批文。本文以2011年1月—2019年12月间我国制药行业上市公司并购事件为样本，对在研新药和可生产药品批文的价值从四个维度度量：是否有在研新药和可生产药品批文；在研新药数量及可生产药品批文数量；根据创新药和仿制药两个类别进行细分；标的企业所拥有的在研新药和可生产药品批文的市场价值。论文发现药品批文对企业并购溢价的影响不是很显著。进一步的，本文探究了药品批文对主并企业的对被并购公司的估值的影响。实证结果表明，我国制药企业在并购估值时确实会考虑到在研新药和可生产药品批文的价值。本文还发现对于可生产药品来说，相对创新药，被并购公司持有的仿制药批文影响更显著。而对于在研新药来说，主并企业更看重在研的创新药，在研仿制药对并购估值的影响不大。最后，本文选取了两个代表性案例进一步分析和探讨药品批文对企业并购的影响。
ContributorsYe, Tao (Author) / Shen, Wei (Thesis advisor) / Chang, Chun (Thesis advisor) / Jiang, Zhan (Committee member) / Gu, Bin (Committee member) / Arizona State University (Publisher)
Created2022
Description汽车行业属于国家支柱型产业，创造了高额的产值，增加了就业岗位。随着汽车生产行业竞争日趋激烈的趋势影响，汽车经销商在未来会出现明显的分化，并且逐步向头部集中。基于这样的行业背景，本项研究开展汽车经销商整体经营和盈利能力等方面的详细深入分析，即系统整合汽车经销商业务运营层面和财务层面数据，结合统计研究方法，对经销商盈利能力进行系统且详实归因分析，从而试别驱动盈利能力的关键业务要素。其研究成果能够完善对行业发展规律和经营模式系统性理解，从而进一步指导该领域的相关业务实践，提高经销商整体经营业绩。本课题通过四个阶段来开展经销商整体经营与盈利归因的相关研究。首先，本课题梳理了中国汽车消费行业发展的历史，同时阐述样本期内（2018-2020年）国内宏观经济和汽车消费市场的特征进行，并介绍X品牌汽车经销商的地理分布、资质和业绩评级体系、自身经营特征以及汽车生产商对经销商扶持政策等方面。在第二阶段，本课题聚焦研究假设、模型与方法，通过对X品牌汽车经销商的业务结构和运营管理开展分析，并逐步识别影响经销商盈利的关键指标变量，并提出研究假设和相关模型（即时间序列模型和面板回归模型）。在第三阶段，本课题首先开展经销商相关信息整体性统计分析，获得关键业务指标在样本期内动态特征，并结合时间序列回归模型探讨各项业务指标对经销商整体盈利能力的影响程度。在第四阶段，本课题采用（个体）固定效应的面板回归模型来研究不同组别（控制）条件下经销商盈利能力的影响因素以及其盈利能力对这些因素的敏感程度，从而更深入和全面地揭示影响经销商盈利能力的潜在因素。
基于上述四阶段的研究结果，本研究进一步就提升经销商盈利能力展开讨论，并提出相应对策。本课题相关结论仅从X品牌汽车经销商经营和财务数据进行定性和定量分析获得，但衷心希望本研究的成果能够对汽车经销商改善经营业务方面能起到实践上的借鉴和指导意义。
ContributorsPan, Guangxiong (Author) / Shen, Wei (Thesis advisor) / Wu, Fei (Thesis advisor) / Zhu, Qigui (Committee member) / Arizona State University (Publisher)
Created2022
Description中小微企业是社会与经济的基本盘，它们面临的贷款融资难是全世界各国家都长期存在的世界难题，已经成了影响中小微企业经营发展的重要问题。以往的学术研究都指出了融资难的根本影响因素，那就是信息不对称，但是以往的专家学者通常是基于理性经济人的假设前提来开展进一步的影响因素研究，本论文尝试从行为金融学的视角来研究中小微企业融资难问题，研究分析贷款过程中的非理性行为因素，为提升小微贷款可获得性寻求新的思路和解决方法。以中小企业融资理论、信息不对称理论和行为金融理论为基础，结合上市银行的披露数据和问卷调查开展实证研究分析，发现企业和银行在中小微贷款融资过程中都存在非理性行为，产生心理授权效应、锚定效应和确定效应，对小微贷款可得性产生显著影响。
建议通过强化企业信用信息开放共享、提升信息披露、加强政策引导、坚持发挥中小银行对小微企业的服务优势、鼓励银行发展金融科技优化提升服务等多种方式，进一步提升小微贷款可得性，缓解中小微企业融资难问题。
ContributorsDeng, Bo (Author) / Huang, Xiaochuan (Thesis advisor) / Wu, Fei (Thesis advisor) / Zheng, Zhiqiang (Committee member) / Arizona State University (Publisher)
Created2022
Description随着全球经济周期的波动，我国经济结构的调整，中美贸易冲突的长期趋势不变，加之新冠疫情导致的全球公共卫生紧急事件的影响，我国的经济环境形势日益严峻。根据最新统计数据显示，截止到2021年4月30日，我国证券交易市场被ST制度处理的ST公司已经超过250家之多，并且还在持续增加。上市公司是我国经济体系的重要组成部分，上市公司陷入困境不仅仅会影响上市公司的所有者，更会影响千千万万的雇佣员工，影响地方经济，影响行业上下游供应链的稳定，影响巨额债券持有者的金融机构投资者和公开交易市场上的大量中小股票投资者。
因此，如何帮助困境上市公司走出困境，实现再复兴就成为了我们迫切需要解决的问题。
随着不少困境上市公司通过破产重整的方式实现了再上市，再复兴，破产重整成为了我们研究困境上市公司实现复兴的重要有效方式。
ContributorsFang, Xiang (Author) / Shao, Benjamin (Thesis advisor) / Jiang, Zhan (Thesis advisor) / Wu, Fei (Committee member) / Arizona State University (Publisher)
Created2022
Description企业文化以及中高层员工对企业文化的认同度影响员工工作绩效表现，探讨他们之间的相互作用机理，有利于厘清企业文化的执行效果，方便决策者根据现实情况进行决策调整。在员工工作绩效层面，受限于数据的易得性、代表性与普遍性，以往的研究更多关注于企业发展，同时，很少有学者关注中高层管理人对企业文化认同的影响及决定因素。青山实业子公司众多，中高层管理人员人数达六百多人，提供了足够的研究样本，正是在这样的背景下，本文从剖析核心企业文化以及中高层管理人员对企业文化认同度视角出发，结合内外部因素，探索企业文化认同度与工作绩效、工作满意度的关系，并确定影响企业文化认同的前因，分析其作用机制，并据此对企业为中高层个人发展提供良好平台提出策略和建议。研究发现，归属感需求，外向型性格，工作能力，组织文化强度，团队沟通，分配公平和企业声誉对于组织文化认同度有正面影响，且这些影响因素在控制常见变量的情况下依然呈现出显著性。企业文化认同度对工作绩效和工作满意度都具有显著的正面促进作用。
ContributorsHe, Xiuqin (Author) / Zhu, David (Thesis advisor) / Wu, Fei (Thesis advisor) / Zhang, Zhen (Committee member) / Arizona State University (Publisher)
Created2022