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Mathematical modeling with applications in high-performance coding.

机译:数学建模及其在高性能编码中的应用。

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摘要

With the progress in scientific research and practical application, mathematical models are being improved continuously to explain the nature and advance the technology. This dissertation involves both theoretical and empirical studies on mathematical modeling. From a theoretical standpoint, it investigates model selection and analysis; from an empirical perspective, it explores channel and source coding.; The question of how to decide among competing explanations of data is at the heart of the scientific enterprise. Choosing competing models based solely on the goodness of fit can result in the selection of an unnecessarily complex model that overfits the data. The dilemma is how to compromise both goodness of fit and model complexity. Among various model selection criteria, the Minimum Description Length (MDL) principle is a relatively recent method for inductive inference, which embodies the principle of Occam's razor. In applying MDL to the selection of parametric models, one of the main obstacles is to calculate Fisher information. This study presents a general formula to compute Fisher information with multinomial or normal distribution for any mathematical model.; Another focus of the current research is on componential analysis, which investigates how and how much each parameter affects mathematical model's ability to fit arbitrary patterns of data. To assess the relative importance of each parameter for such an ability is critical to both model selection and model building. The goal of the research along this venue is to establish a unified theory, under which complex modeling procedures can be analyzed in terms of the contribution of each parameter.; Essentially, coding is the direct implementation of mathematical modeling. Channel coding and source coding are the practical applications of two important concepts in the information theory: channel capacity and entropy. This study examines these concepts in two particular cases respectively: bandwidth efficient nonsystematic turbo codes and bitmap index compression through an integrated reorganization.; The investigation starts with an introduction on mathematical modeling and the overview of the study. It is then organized by four consecutive themes in the following chapters: MDL model selection, componential analysis, turbo codes, and bitmap compression.
机译:随着科学研究和实际应用的发展,数学模型也在不断改进,以解释其本质并推动技术的发展。本文涉及数学建模的理论研究和实证研究。从理论上讲,它研究模型的选择和分析。从经验的角度,它探讨了通道和源代码编码。如何在竞争的数据解释之间做出决定的问题是科学事业的核心。仅基于拟合优度来选择竞争模型可能会导致选择不必要的,过于拟合数据的复杂模型。难题是如何兼顾拟合优度和模型复杂性。在各种模型选择标准中,最小描述长度(MDL)原理是一种相对较新的归纳推理方法,体现了Occam剃刀的原理。在将MDL应用于参数模型的选择时,主要障碍之一是计算Fisher信息。这项研究提出了一个通用公式,可以为任何数学模型计算具有多项式或正态分布的Fisher信息。当前研究的另一个重点是成分分析,它研究了每个参数如何以及在多大程度上影响数学模型拟合任意数据模式的能力。评估每个参数对于这种能力的相对重要性对于模型选择和模型构建都是至关重要的。在此场所进行研究的目的是建立一个统一的理论,在该理论下可以根据每个参数的贡献来分析复杂的建模过程。本质上,编码是数学建模的直接实现。信道编码和源编码是信息理论中两个重要概念的实际应用:信道容量和熵。这项研究分别在两种特定情况下研究了这些概念:带宽有效的非系统Turbo码和通过集成重组的位图索引压缩。该研究从数学建模导论和研究概述开始。然后,在以下各章中按四个连续的主题进行组织:MDL模型选择,组件分析,turbo代码和位图压缩。

著录项

  • 作者

    Su, Yong.;

  • 作者单位

    The Ohio State University.;

  • 授予单位 The Ohio State University.;
  • 学科 Engineering Electronics and Electrical.
  • 学位 Ph.D.
  • 年度 2005
  • 页码 130 p.
  • 总页数 130
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 无线电电子学、电信技术;
  • 关键词

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