Advertisement

Fractal Image Compression: Theory and Applications

  •  5星
  •     浏览量: 0
  •     大小:None
  •      文件类型:DJVU


简介:
《Fractal Image Compression: Theory and Applications》深入探讨了分形图像压缩技术的基本理论及其在实际应用中的实现方法。 这本书介绍了基于图像自变换的新图像压缩方法的理论与应用。这些方法将图像表示为一个分形对象——即在所有尺度上都有细节的对象。本书非常实用且完全更新,可作为从事图像处理及编码工作的人员的重要参考书,并为那些对分形不熟悉的读者提供很好的入门介绍。书中以简单的形式介绍了分形图像压缩的概念,并详细描述了与主题相关的数学理论。

全部评论 (0)

还没有任何评论哟~
客服
客服
  • Fractal Image Compression: Theory and Applications
    优质
    《Fractal Image Compression: Theory and Applications》深入探讨了分形图像压缩技术的基本理论及其在实际应用中的实现方法。 这本书介绍了基于图像自变换的新图像压缩方法的理论与应用。这些方法将图像表示为一个分形对象——即在所有尺度上都有细节的对象。本书非常实用且完全更新,可作为从事图像处理及编码工作的人员的重要参考书,并为那些对分形不熟悉的读者提供很好的入门介绍。书中以简单的形式介绍了分形图像压缩的概念,并详细描述了与主题相关的数学理论。
  • H-Transforms: Theory and Applications
    优质
    H-Transforms: Theory and Applications是一本深入探讨H变换理论及其应用的专著,涵盖了数学、工程等多个领域的最新研究成果。 这本关于H变换理论与应用的电子书是高清最新版本的经典著作,为英文版。
  • Fuzzy Modeling and Control: Theory and Applications
    优质
    《Fuzzy Modeling and Control: Theory and Applications》是一本探讨模糊模型与控制理论及其应用的专业书籍,深入剖析了模糊逻辑在控制系统中的作用。 这本书涵盖了从系统建模到控制器设计的广泛内容,并包含一系列有趣的应用案例。全书分为三个部分:第一部分专注于描述模糊建模技术。
  • Network Flows: Theory, Algorithms, and Applications
    优质
    《Network Flows: Theory, Algorithms, and Applications》全面介绍了网络流理论及其算法和应用,是研究图论、组合优化等领域的重要参考书。 非扫描版《春》电子书 NETWORK FLOWS 理论、算法及应用 作者:VINDRA K. AHUJA, THOMAS L. MAGNANT, JAMES B. ORLIN
  • Adaptive Filters: Theory and Applications (2nd Edition)
    优质
    《自适应滤波器:理论与应用(第2版)》全面介绍了自适应信号处理的基础理论和最新技术,涵盖各种算法及其工程实现。 Adaptive Filters. Theory and Applications, 2nd edition 这本书是关于自适应滤波器理论与应用的第二版。书中详细介绍了自适应滤波技术的基本原理及其在各种实际问题中的应用,涵盖了从基础概念到高级算法的所有内容,并提供了大量实例和案例研究来帮助读者深入理解这些复杂的技术。
  • Model-Free Adaptive Control: Theory and Applications
    优质
    《Model-Free Adaptive Control: Theory and Applications》一书全面介绍了无模型自适应控制理论及其在各个领域的应用实践,为复杂系统的控制问题提供了创新解决方案。 by Hou, Zhongsheng Jin, Shangtai Introduction ...........................................................................................1 1. Model-Based Control ........................................................................ 1 1.1 Modeling and Identification ......................................................... 1 1.2 Model-Based Controller Design ...................................................3 2. Data-Driven Control .........................................................................5 2.1 Definition and Motivation of Data-Driven Control .....................6 2.2 Object of Data-Driven Control Methods..............................7 2.3 Necessity of Data-Driven Control Theory and Methods ....8 2.4 Brief Survey on Data-Driven Control Methods..................10 2.5 Summary of Data-Driven Control Methods.......................15 3. Preview of the Book.........................................................................16 Recursive Parameter Estimation for Discrete-Time Systems................ 19 2. Introduction ....................................................................................19 2. Parameter Estimation Algorithm for LinearlyParameterized Systems.............................................................20 2.1 Projection Algorithm..........................................................21 2.2 Least-Squares Algorithm ....................................................22 3. Parameter Estimation Algorithm for NonlinearlyParameterized Systems..............................................27 3.1 Projection Algorithm and Its Modified Formfor Nonlinearly Parameterized Systems...............................27 3.2 Least-Squares Algorithm and Its Modified Formfor Nonlinearly Parameterized Systems...............................32 4. Conclusions.................................................................................... 44 Dynamic Linearization Approach of Discrete-TimeNonlinear Systems..............................................45 1. Introduction ....................................................................................45 2. SISO Discrete-Time Nonlinear Systems ..........................................47 2.1 Compact Form Dynamic Linearization..............................47 2.2 Partial Form Dynamic Linearization..................................53 2.3 Full Form Dynamic Linearization......................................59 3. MIMO Discrete-Time Nonlinear Systems......................................64 3.1 Compact Form Dynamic Linearization.............................64 3.2 Partial Form Dynamic Linearization.................................66 3.3 Full Form Dynamic Linearization......................................69 4. Conclusions.....................................................................................71 Model-Free Adaptive Control of SISO Discrete-TimeNonlinear Systems...........................................75 1. Introduction ....................................................................................75 2. CFDL Data Model Based MFAC ................................................... 77 2.1 Control System Design...................................................... 77 2.2 Stability Analysis ................................................................80 2.3 Simulation Results..............................................................87 3. PFDL Data Model Based MFAC.....................................................93 3.1 Control System Design.......................................................93 3.2 Stability Analysis ................................................................96 3.3 Simulation Results............................................................104 4. FFDL Data Model Based MFAC...................................................108 4.1 Control System Design.....................................................108 4.2 Simulation Results............................................................113 5. Conclusions................................................................................... 118 Model-Free Adaptive Control of MIMO Discrete-TimeNonlinear Systems..............................................119 1. Introduction .................................................................................. 119 2. CFDL Data Model Based MFAC ..................................................120 2.1 Control System Design.....................................................120 2.2 Stability Analysis ..............................................................124 2.3 Simulation Results............................................................132
  • Theory for Stochastic Processes and Their Applications
    优质
    本书《随机过程理论及其应用》深入探讨了随机过程的基础理论,并展示了这些理论在解决实际问题中的广泛应用。 《随机过程:理论及其应用》(作者Robert G. Gallager)的习题解答。
  • Kalman Filtering: Theory and Applications with MATLAB
    优质
    本书深入浅出地介绍了卡尔曼滤波理论及其应用,并通过MATLAB进行实例演示,适合工程技术人员和高校师生阅读参考。 关于Kalman滤波的书籍介绍了多种Kalman滤波器及其在Matlab中的实现方法。
  • Theory, Methods, and Applications of Topology Optimization
    优质
    本论文集探讨了拓扑优化领域的理论、方法及其应用。涵盖了从基础理论到实际问题解决的全面内容,为研究人员和工程师提供了宝贵的资源。 这是一本经典的结构拓扑优化入门电子书。