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1. |
Record Nr. |
UNINA9910457254903321 |
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Autore |
Mishra Jibitesh |
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Titolo |
L-system fractals [[electronic resource] /] / J. Mishra, S.N. Mishra |
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Pubbl/distr/stampa |
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Amsterdam ; ; Boston, MA, : Elsevier B. V., 2007 |
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ISBN |
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1-280-75187-8 |
9786610751877 |
0-08-046938-8 |
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Descrizione fisica |
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1 online resource (274 p.) |
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Collana |
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Mathematics in science and engineering ; ; v. 209 |
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Altri autori (Persone) |
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MishraS. N (Sarojananda N.) |
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Disciplina |
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Soggetti |
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Computer vision |
L systems |
Fractals |
Electronic books. |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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Description based upon print version of record. |
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Nota di bibliografia |
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Includes bibliographical references and index. |
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Nota di contenuto |
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Cover; Copyright Page; Preface; Table of Contents; Chapter 1 Introduction to Fractals; 1.1 Overview of fractals; 1.2 Fractals vs. Computer Graphics; 1.2.1 Chaotic Systems; 1.2.2 Strange Attractor; 1.2.3 Newton Raphson; 1.3 Fractal Geometry; 1.4 Categories of Fractals; 1.4.1 Geometrical fractals; 1.4.2 Algebraic fractals; 1.4.3 Stochastic fractals; 1.5 Fractals and Non-fractal Objects; 1.5.1 The sizes of the features of the fractal and non-fractal objects; 1.5.2 The four measure properties of fractal; 1.6 Defining a fractal; 1.6.1 Definitions of related terms; 1.6.2 Definition of fractal |
1.7 Applications for Fractals1.8 Summary; Chapter 2 Fractals and L-System; 2.1 Reviews on L-system; 2.2 Parallel grammars: A phenomenon; 2.3 L-Systems; 2.3.1 D0L-system; 2.3.2 Fractals and graphic interpretation of strings; 2.3.3 Bracketed L-systems and models of plants architecture; 2.3.4 L-systems and Genetic Algorithms; 2.4 Basic definitions of L-Systems; 2.4.1 Fibonacci L-system; 2.4.2 Types of L-systems; 2.4.3 Thue-Morse L-system; 2.4.4 Paper folding and the Dragon curve; 2.5 Turtle graphics and L-systems; 2.5.1 Branching and bracketed L-systems |
2.5.2 Famous L-systems of mathematical history2.5.3 Self-similarity |
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and scaling; 2.6 Summary; Chapter 3 Interactive Generation of Fractal Images; 3.1 IFS and Fractals; 3.2 Generation of Fractals; 3.2.1 Multi Lens Copy Machines; 3.3 Computer Implementation; 3.3.1 The Random Algorithm; 3.4 Designing Fractals; 3.4.1 How does the program work; 3.5 Software Package; 3.5.1 Background; 3.5.2 Computer Implementation; 3.5.3 Sample Output; 3.6 Mathematical Expression of IFS; 3.6.1 RIFS; 3.6.2 Modified MRCM; 3.7 Summary; Chapter 4 Generation of a Class of Hybrid Fractals; 4.1 Background |
4.1.1 Parallel grammar: A critical review4.1.2 Rules for biological phenomenon; 4.1.3 Some definitions and examples; 4.1.4 Applications of L-System; 4.1.5 Turtle graphics vs L-System; 4.1.6 Generation of fractal figures; 4.1.7 About L-System; 4.1.8 An L-system example; 4.1.9 Representing mathematical sequence in L-System; 4.2 The Approach; 4.2.1 Assumptions; 4.2.2 Combination of L-Systems; 4.2.3 The new L-System or the Hybrid L-System; 4.2.4 The Algorithm; 4.3 Experimentally Generated Fractals; 4.3.1 Fractal figures for Fibonacci sequence and Koch curve |
4.3.2 Fractal figures for Mathematical series 1 to n and Koch curve4.3.3 Fractal figures based on different combinations; 4.4 Variation on Koch Curves; 4.5 Fractals with other Mathematical Sequences; 4.6 Interpretation of Result; 4.6.1 Comparison of Koch curve with Hybrid system; 4.6.2 Arbitrary Figures; 4.7 Summary; Chapter 5 L-System Strings from Ramification Matrix; 5.1 Definition of Terms; 5.1.1 Modules; 5.1.2 Productions; 5.2 Parallel Rewriting Systems; 5.3 An Elementary L-System Parser; 5.3.1 The structure of an L-System module; 5.3.2 L-System strings |
5.3.3 Rewriting the L-System string |
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Sommario/riassunto |
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The book covers all the fundamental aspects of generating fractals through L-system. Also it provides insight to various researches in this area for generating fractals through L-system approach & estimating dimensions. Also it discusses various applications of L-system fractals. Key Features: - Fractals generated from L-System including hybrid fractals - Dimension calculation for L-system fractals - Images & codes for L-system fractals - Research directions in the area of L-system fractals - Usage of various freely downloadable tools in this area - Frac |
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2. |
Record Nr. |
UNINA9910821592603321 |
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Autore |
Ghannouchi Fadhel M. <1958-> |
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Titolo |
Behavioral modelling and predistortion of wideband wireless transmitters / / Fadhel Ghannouchi, Oualid Hammi, Mohamed Helaoui |
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Pubbl/distr/stampa |
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Chichester, England : , : Wiley, , 2015 |
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©2015 |
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ISBN |
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1-119-00444-6 |
1-119-00442-X |
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Edizione |
[1st edition] |
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Descrizione fisica |
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1 online resource (272 p.) |
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Disciplina |
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Soggetti |
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Wireless communication systems - Mathematical models |
Broadband communication systems - Mathematical models |
Signal theory (Telecommunication) - Mathematics |
Telecommunication - Transmitters and transmission - Mathematics |
Nonlinear systems - Mathematical models |
Electric distortion - Mathematical models |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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Description based upon print version of record. |
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Nota di bibliografia |
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Includes bibliographical references at the end of each chapters and index. |
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Nota di contenuto |
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Cover; Title Page; Copyright; Contents; About the Authors; Preface; Acknowledgments; Chapter 1 Characterization of Wireless Transmitter Distortions; 1.1 Introduction; 1.1.1 RF Power Amplifier Nonlinearity; 1.1.2 Inter-Modulation Distortion and Spectrum Regrowth; 1.2 Impact of Distortions on Transmitter Performances; 1.3 Output Power versus Input Power Characteristic; 1.4 AM/AM and AM/PM Characteristics; 1.5 1 dB Compression Point; 1.6 Third and Fifth Order Intercept Points; 1.7 Carrier to Inter-Modulation Distortion Ratio; 1.8 Adjacent Channel Leakage Ratio; 1.9 Error Vector Magnitude |
ReferencesChapter 2 Dynamic Nonlinear Systems; 2.1 Classification of Nonlinear Systems; 2.1.1 Memoryless Systems; 2.1.2 Systems with Memory; 2.2 Memory in Microwave Power Amplification Systems; 2.2.1 Nonlinear Systems without Memory; 2.2.2 Weakly Nonlinear and Quasi-Memoryless Systems; 2.2.3 Nonlinear System with Memory; 2.3 Baseband and Low-Pass Equivalent Signals; 2.4 Origins and Types of |
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Memory Effects in Power Amplification Systems; 2.4.1 Origins of Memory Effects; 2.4.2 Electrical Memory Effects; 2.4.3 Thermal Memory Effects; 2.5 Volterra Series Models; References |
Chapter 3 Model Performance Evaluation3.1 Introduction; 3.2 Behavioral Modeling versus Digital Predistortion; 3.3 Time Domain Metrics; 3.3.1 Normalized Mean Square Error; 3.3.2 Memory Effects Modeling Ratio; 3.4 Frequency Domain Metrics; 3.4.1 Frequency Domain Normalized Mean Square Error; 3.4.2 Adjacent Channel Error Power Ratio; 3.4.3 Weighted Error Spectrum Power Ratio; 3.4.4 Normalized Absolute Mean Spectrum Error; 3.5 Static Nonlinearity Cancelation Techniques; 3.5.1 Static Nonlinearity Pre-Compensation Technique; 3.5.2 Static Nonlinearity Post-Compensation Technique |
3.5.3 Memory Effect Intensity3.6 Discussion and Conclusion; References; Chapter 4 Quasi-Memoryless Behavioral Models; 4.1 Introduction; 4.2 Modeling and Simulation of Memoryless/Quasi-Memoryless Nonlinear Systems; 4.3 Bandpass to Baseband Equivalent Transformation; 4.4 Look-Up Table Models; 4.4.1 Uniformly Indexed Loop-Up Tables; 4.4.2 Non-Uniformly Indexed Look-Up Tables; 4.5 Generic Nonlinear Amplifier Behavioral Model; 4.6 Empirical Analytical Based Models; 4.6.1 Polar Saleh Model; 4.6.2 Cartesian Saleh Model; 4.6.3 Frequency-Dependent Saleh Model; 4.6.4 Ghorbani Model |
4.6.5 Berman and Mahle Phase Model4.6.6 Thomas-Weidner-Durrani Amplitude Model; 4.6.7 Limiter Model; 4.6.8 ARCTAN Model; 4.6.9 Rapp Model; 4.6.10 White Model; 4.7 Power Series Models; 4.7.1 Polynomial Model; 4.7.2 Bessel Function Based Model; 4.7.3 Chebyshev Series Based Model; 4.7.4 Gegenbauer Polynomials Based Model; 4.7.5 Zernike Polynomials Based Model; References; Chapter 5 Memory Polynomial Based Models; 5.1 Introduction; 5.2 Generic Memory Polynomial Model Formulation; 5.3 Memory Polynomial Model; 5.4 Variants of the Memory Polynomial Model; 5.4.1 Orthogonal Memory Polynomial Model |
5.4.2 Sparse-Delay Memory Polynomial Model |
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Sommario/riassunto |
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Covers theoretical and practical aspects related to the behavioral modelling and predistortion of wireless transmitters and power amplifiers. It includes simulation software that enables the users to apply the theory presented in the book. In the first section, the reader is given the general background of nonlinear dynamic systems along with their behavioral modelling from all its aspects. In the second part, a comprehensive compilation of behavioral models formulations and structures is provided including memory polynomial based models, box oriented models such as Hammerstein-based and Wiener-based models, and neural networks-based models. The book will be a valuable resource for design engineers, industrial engineers, applications engineers, postgraduate students, and researchers working on power amplifiers modelling, linearization, and design. |
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