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Arithmetic circuits for DSP applications / / edited by Pramod Kumar Meher and Thanos Stouraitis
| Arithmetic circuits for DSP applications / / edited by Pramod Kumar Meher and Thanos Stouraitis |
| Pubbl/distr/stampa | Hoboken, New Jersey : , : IEEE Press : , : Wiley, , [2017] |
| Descrizione fisica | 1 PDF : illustrations |
| Disciplina | 621.382/20151 |
| Soggetto topico |
Signal processing - Digital techniques - Mathematics
Electronic digital computers - Circuits |
| ISBN |
1-119-20678-2
1-119-20679-0 1-119-20680-4 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Series Page; Title Page; Copyright; Preface; About The Editors; Chapter 1: Basic Arithmetic Circuits; 1.1 Introduction; 1.2 Addition and Subtraction; 1.3 Multiplication; 1.4 Sum-of-Products Circuits; 1.5 Squaring; 1.6 Complex Multiplication; 1.7 Special Functions; References; Chapter 2: Shift-Add Circuits for Constant Multiplications; 2.1 Introduction; 2.2 Representation of Constants; 2.3 Single Constant Multiplication; 2.4 Algorithms for Multiple Constant Multiplications; 2.5 Optimization Schemes and Optimal Algorithms; 2.6 Applications; 2.7 Pitfalls and Scope for Future Work
2.8 ConclusionsReferences; Chapter 3: DA-Based Circuits for Inner-Product Computation; 3.1 Introduction; 3.2 Mathematical Foundation and Concepts; 3.3 Techniques for Area Optimization of DA-Based Implementations; 3.4 Techniques for Performance Optimization of DA-Based Implementations; 3.5 Techniques for Low Power and Reconfigurable Realization of DA-Based Implementations; 3.6 Conclusion; References; Chapter 4: Table-Based Circuits for DSP Applications; 4.1 Introduction; 4.2 LUT Design for Implementation of Boolean Function; 4.3 Lookup Table Design for Constant Multiplication 4.4 Evaluation of Elementary Arithmetic Functions4.5 Applications; 4.6 Summary; References; Chapter 5: CORDIC Circuits; 5.1 Introduction; 5.2 Basic CORDIC Techniques; 5.3 Advanced CORDIC Algorithms and Architectures; 5.4 Scaling, Quantization, and Accuracy Issues; 5.5 Applications of CORDIC; 5.6 Conclusions; References; Chapter 6: RNS-Based Arithmetic Circuits and Applications; 6.1 Introduction; 6.2 Modulo Addition and Subtraction; 6.3 Modulo Multiplication and Modulo Squaring; 6.4 Forward (binary to RNS) Conversion; 6.5 RNS to Binary Conversion; 6.6 Scaling and Base Extension 6.7 Magnitude Comparison and Sign Detection6.8 Error Correction and Detection; 6.9 Applications of RNS; References; Chapter 7: Logarithmic Number System; 7.1 Introduction; 7.2 Basics of LNS Representation; 7.3 Fundamental Arithmetic Operations; 7.4 Forward and Inverse Conversion; 7.5 Complex Arithmetic in LNS; 7.6 LNS Processors; 7.7 LNS for Low-Power Dissipation; 7.8 Applications; 7.9 Conclusions; References; Chapter 8: Redundant Number System-Based Arithmetic Circuits; 8.1 Introduction; 8.2 Fundamentals of Redundant Number Systems; 8.3 Redundant Number Systems 8.4 Basic Arithmetic Circuits for Redundant Number Systems8.5 Binary to Redundant Conversion and the Reverse; 8.6 Special Arithmetic Circuits for Redundant Number Systems; 8.7 Applications; 8.8 Summary and Further Reading; References; Index; End User License Agreement |
| Record Nr. | UNINA-9910271057903321 |
| Hoboken, New Jersey : , : IEEE Press : , : Wiley, , [2017] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Arithmetic circuits for DSP applications / / edited by Pramod Kumar Meher and Thanos Stouraitis
| Arithmetic circuits for DSP applications / / edited by Pramod Kumar Meher and Thanos Stouraitis |
| Pubbl/distr/stampa | Hoboken, New Jersey : , : IEEE Press : , : Wiley, , [2017] |
| Descrizione fisica | 1 PDF : illustrations |
| Disciplina | 621.382/20151 |
| Soggetto topico |
Signal processing - Digital techniques - Mathematics
Electronic digital computers - Circuits |
| ISBN |
1-119-20678-2
1-119-20679-0 1-119-20680-4 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Series Page; Title Page; Copyright; Preface; About The Editors; Chapter 1: Basic Arithmetic Circuits; 1.1 Introduction; 1.2 Addition and Subtraction; 1.3 Multiplication; 1.4 Sum-of-Products Circuits; 1.5 Squaring; 1.6 Complex Multiplication; 1.7 Special Functions; References; Chapter 2: Shift-Add Circuits for Constant Multiplications; 2.1 Introduction; 2.2 Representation of Constants; 2.3 Single Constant Multiplication; 2.4 Algorithms for Multiple Constant Multiplications; 2.5 Optimization Schemes and Optimal Algorithms; 2.6 Applications; 2.7 Pitfalls and Scope for Future Work
2.8 ConclusionsReferences; Chapter 3: DA-Based Circuits for Inner-Product Computation; 3.1 Introduction; 3.2 Mathematical Foundation and Concepts; 3.3 Techniques for Area Optimization of DA-Based Implementations; 3.4 Techniques for Performance Optimization of DA-Based Implementations; 3.5 Techniques for Low Power and Reconfigurable Realization of DA-Based Implementations; 3.6 Conclusion; References; Chapter 4: Table-Based Circuits for DSP Applications; 4.1 Introduction; 4.2 LUT Design for Implementation of Boolean Function; 4.3 Lookup Table Design for Constant Multiplication 4.4 Evaluation of Elementary Arithmetic Functions4.5 Applications; 4.6 Summary; References; Chapter 5: CORDIC Circuits; 5.1 Introduction; 5.2 Basic CORDIC Techniques; 5.3 Advanced CORDIC Algorithms and Architectures; 5.4 Scaling, Quantization, and Accuracy Issues; 5.5 Applications of CORDIC; 5.6 Conclusions; References; Chapter 6: RNS-Based Arithmetic Circuits and Applications; 6.1 Introduction; 6.2 Modulo Addition and Subtraction; 6.3 Modulo Multiplication and Modulo Squaring; 6.4 Forward (binary to RNS) Conversion; 6.5 RNS to Binary Conversion; 6.6 Scaling and Base Extension 6.7 Magnitude Comparison and Sign Detection6.8 Error Correction and Detection; 6.9 Applications of RNS; References; Chapter 7: Logarithmic Number System; 7.1 Introduction; 7.2 Basics of LNS Representation; 7.3 Fundamental Arithmetic Operations; 7.4 Forward and Inverse Conversion; 7.5 Complex Arithmetic in LNS; 7.6 LNS Processors; 7.7 LNS for Low-Power Dissipation; 7.8 Applications; 7.9 Conclusions; References; Chapter 8: Redundant Number System-Based Arithmetic Circuits; 8.1 Introduction; 8.2 Fundamentals of Redundant Number Systems; 8.3 Redundant Number Systems 8.4 Basic Arithmetic Circuits for Redundant Number Systems8.5 Binary to Redundant Conversion and the Reverse; 8.6 Special Arithmetic Circuits for Redundant Number Systems; 8.7 Applications; 8.8 Summary and Further Reading; References; Index; End User License Agreement |
| Record Nr. | UNINA-9910829843103321 |
| Hoboken, New Jersey : , : IEEE Press : , : Wiley, , [2017] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Probability and random processes [[electronic resource] ] : with applications to signal processing and communications / / Scott L. Miller, Donald Childers
| Probability and random processes [[electronic resource] ] : with applications to signal processing and communications / / Scott L. Miller, Donald Childers |
| Autore | Miller Scott L |
| Edizione | [Ed. 2.] |
| Pubbl/distr/stampa | Waltham, Mass., : Elsevier, 2012 |
| Descrizione fisica | 1 online resource (625 p.) |
| Disciplina | 621.382/20151 |
| Altri autori (Persone) | ChildersDonald G |
| Soggetto topico |
Signal processing - Mathematics
Probabilities Stochastic processes |
| Soggetto genere / forma | Electronic books. |
| ISBN |
1-283-41027-3
9786613410276 0-12-387013-5 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Front Cover; Probability and Random Processes: With Applications to Signal Processingand Communications; Copyright; Contents; Preface; Chapter 1: Introduction; 1.1 A Speech Recognition System; 1.2 A Radar System; 1.3 A Communication Network; Chapter 2: Introduction to Probability Theory; 2.1 Experiments, Sample Spaces, and Events; 2.2 Axioms of Probability; 2.3 Assigning Probabilities; 2.4 Joint and Conditional Probabilities; 2.5 Basic Combinatorics; 2.6 Bayes's Theorem; 2.7 Independence; 2.8 Discrete Random Variables; 2.9 Engineering Application-An Optical Communication System; Exercises
Section 2.1: Experiments, Sample Spaces, and EventsSection 2.2: Axioms of Probability; Section 2.3: Assigning Probabilities; Section 2.4: Joint and Conditional Probabilities; Section 2.5: Basic Combinatorics; Section 2.6: Bayes's Theorem; Section 2.7: Independence; Section 2.8: Discrete Random Variables; Miscellaneous Problems; MATLAB Exercises; Chapter 3: Random Variables, Distributions,and Density Functions; 3.1 The Cumulative Distribution Function; 3.2 The Probability Density Function; 3.3 The Gaussian Random Variable; 3.4 Other Important Random Variables; 3.4.1 Uniform Random Variable 3.4.2 Exponential Random Variable3.4.3 Laplace Random Variable; 3.4.4 Gamma Random Variable; 3.4.5 Erlang Random Variable; 3.4.6 Chi-Squared Random Variable; 3.4.7 Rayleigh Random Variable; 3.4.8 Rician Random Variable; 3.4.9 Cauchy Random Variable; 3.5 Conditional Distribution and Density Functions; 3.6 Engineering Application: Reliability and Failure Rates; Exercises; Section 3.1: The Cumulative Distribution Function; Section 3.2: The Probability Density Function; Section 3.3: The Gaussian Random Variable; Section 3.4: Other Important Random Variables Section 3.5: Conditional Distribution and Density FunctionsSection 3.6: Reliability and Failure Rates; Miscellaneous Exercises; MATLAB Exercises; Chapter 4: Operations on a Single Random Variable; 4.1 Expected Value of a Random Variable; 4.2 Expected Values of Functions of Random Variables; 4.3 Moments; 4.4 Central Moments; 4.5 Conditional Expected Values; 4.6 Transformations of Random Variables; 4.6.1 Monotonically Increasing Functions; 4.6.2 Monotonically Decreasing Functions; 4.6.3 Nonmonotonic Functions; 4.7. Characteristic Functions; 4.8. Probability-Generating Functions 4.9 Moment-Generating Functions4.10 Evaluating Tail Probabilities; 4.11 Engineering Application-Scalar Quantization; 4.12 Engineering Application-Entropy and Source Coding; Exercises; Section 4.1: Expected Values of a Random Variable; Section 4.2: Expected Values of Functions of a Random Variable; Section 4.3: Moments; Section 4.4: Central Moments; Section 4.5: Conditional Expected Values; Section 4.6: Transformations of Random Variables; Section 4.7: Characteristic Functions; Section 4.8: Probability-Generating Functions; Section 4.9: Moment-Generating Functions Section 4.10: Evaluating Tail Probabilities |
| Record Nr. | UNINA-9910458157803321 |
Miller Scott L
|
||
| Waltham, Mass., : Elsevier, 2012 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Probability and random processes [[electronic resource] ] : with applications to signal processing and communications / / Scott L. Miller, Donald Childers
| Probability and random processes [[electronic resource] ] : with applications to signal processing and communications / / Scott L. Miller, Donald Childers |
| Autore | Miller Scott L |
| Edizione | [Ed. 2.] |
| Pubbl/distr/stampa | Waltham, Mass., : Elsevier, 2012 |
| Descrizione fisica | 1 online resource (625 p.) |
| Disciplina | 621.382/20151 |
| Altri autori (Persone) | ChildersDonald G |
| Soggetto topico |
Signal processing - Mathematics
Probabilities Stochastic processes |
| ISBN |
1-283-41027-3
9786613410276 0-12-387013-5 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Front Cover; Probability and Random Processes: With Applications to Signal Processingand Communications; Copyright; Contents; Preface; Chapter 1: Introduction; 1.1 A Speech Recognition System; 1.2 A Radar System; 1.3 A Communication Network; Chapter 2: Introduction to Probability Theory; 2.1 Experiments, Sample Spaces, and Events; 2.2 Axioms of Probability; 2.3 Assigning Probabilities; 2.4 Joint and Conditional Probabilities; 2.5 Basic Combinatorics; 2.6 Bayes's Theorem; 2.7 Independence; 2.8 Discrete Random Variables; 2.9 Engineering Application-An Optical Communication System; Exercises
Section 2.1: Experiments, Sample Spaces, and EventsSection 2.2: Axioms of Probability; Section 2.3: Assigning Probabilities; Section 2.4: Joint and Conditional Probabilities; Section 2.5: Basic Combinatorics; Section 2.6: Bayes's Theorem; Section 2.7: Independence; Section 2.8: Discrete Random Variables; Miscellaneous Problems; MATLAB Exercises; Chapter 3: Random Variables, Distributions,and Density Functions; 3.1 The Cumulative Distribution Function; 3.2 The Probability Density Function; 3.3 The Gaussian Random Variable; 3.4 Other Important Random Variables; 3.4.1 Uniform Random Variable 3.4.2 Exponential Random Variable3.4.3 Laplace Random Variable; 3.4.4 Gamma Random Variable; 3.4.5 Erlang Random Variable; 3.4.6 Chi-Squared Random Variable; 3.4.7 Rayleigh Random Variable; 3.4.8 Rician Random Variable; 3.4.9 Cauchy Random Variable; 3.5 Conditional Distribution and Density Functions; 3.6 Engineering Application: Reliability and Failure Rates; Exercises; Section 3.1: The Cumulative Distribution Function; Section 3.2: The Probability Density Function; Section 3.3: The Gaussian Random Variable; Section 3.4: Other Important Random Variables Section 3.5: Conditional Distribution and Density FunctionsSection 3.6: Reliability and Failure Rates; Miscellaneous Exercises; MATLAB Exercises; Chapter 4: Operations on a Single Random Variable; 4.1 Expected Value of a Random Variable; 4.2 Expected Values of Functions of Random Variables; 4.3 Moments; 4.4 Central Moments; 4.5 Conditional Expected Values; 4.6 Transformations of Random Variables; 4.6.1 Monotonically Increasing Functions; 4.6.2 Monotonically Decreasing Functions; 4.6.3 Nonmonotonic Functions; 4.7. Characteristic Functions; 4.8. Probability-Generating Functions 4.9 Moment-Generating Functions4.10 Evaluating Tail Probabilities; 4.11 Engineering Application-Scalar Quantization; 4.12 Engineering Application-Entropy and Source Coding; Exercises; Section 4.1: Expected Values of a Random Variable; Section 4.2: Expected Values of Functions of a Random Variable; Section 4.3: Moments; Section 4.4: Central Moments; Section 4.5: Conditional Expected Values; Section 4.6: Transformations of Random Variables; Section 4.7: Characteristic Functions; Section 4.8: Probability-Generating Functions; Section 4.9: Moment-Generating Functions Section 4.10: Evaluating Tail Probabilities |
| Record Nr. | UNINA-9910778937503321 |
|
Miller Scott L
|
||
| Waltham, Mass., : Elsevier, 2012 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Probability and random processes : with applications to signal processing and communications / / Scott L. Miller, Donald Childers
| Probability and random processes : with applications to signal processing and communications / / Scott L. Miller, Donald Childers |
| Autore | Miller Scott L |
| Edizione | [Ed. 2.] |
| Pubbl/distr/stampa | Waltham, Mass., : Elsevier, 2012 |
| Descrizione fisica | 1 online resource (625 p.) |
| Disciplina |
621.382/20151
621.38220151 |
| Altri autori (Persone) | ChildersDonald G |
| Soggetto topico |
Signal processing - Mathematics
Probabilities Stochastic processes |
| ISBN |
9786613410276
9781283410274 1283410273 9780123870131 0123870135 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Front Cover; Probability and Random Processes: With Applications to Signal Processingand Communications; Copyright; Contents; Preface; Chapter 1: Introduction; 1.1 A Speech Recognition System; 1.2 A Radar System; 1.3 A Communication Network; Chapter 2: Introduction to Probability Theory; 2.1 Experiments, Sample Spaces, and Events; 2.2 Axioms of Probability; 2.3 Assigning Probabilities; 2.4 Joint and Conditional Probabilities; 2.5 Basic Combinatorics; 2.6 Bayes's Theorem; 2.7 Independence; 2.8 Discrete Random Variables; 2.9 Engineering Application-An Optical Communication System; Exercises
Section 2.1: Experiments, Sample Spaces, and EventsSection 2.2: Axioms of Probability; Section 2.3: Assigning Probabilities; Section 2.4: Joint and Conditional Probabilities; Section 2.5: Basic Combinatorics; Section 2.6: Bayes's Theorem; Section 2.7: Independence; Section 2.8: Discrete Random Variables; Miscellaneous Problems; MATLAB Exercises; Chapter 3: Random Variables, Distributions,and Density Functions; 3.1 The Cumulative Distribution Function; 3.2 The Probability Density Function; 3.3 The Gaussian Random Variable; 3.4 Other Important Random Variables; 3.4.1 Uniform Random Variable 3.4.2 Exponential Random Variable3.4.3 Laplace Random Variable; 3.4.4 Gamma Random Variable; 3.4.5 Erlang Random Variable; 3.4.6 Chi-Squared Random Variable; 3.4.7 Rayleigh Random Variable; 3.4.8 Rician Random Variable; 3.4.9 Cauchy Random Variable; 3.5 Conditional Distribution and Density Functions; 3.6 Engineering Application: Reliability and Failure Rates; Exercises; Section 3.1: The Cumulative Distribution Function; Section 3.2: The Probability Density Function; Section 3.3: The Gaussian Random Variable; Section 3.4: Other Important Random Variables Section 3.5: Conditional Distribution and Density FunctionsSection 3.6: Reliability and Failure Rates; Miscellaneous Exercises; MATLAB Exercises; Chapter 4: Operations on a Single Random Variable; 4.1 Expected Value of a Random Variable; 4.2 Expected Values of Functions of Random Variables; 4.3 Moments; 4.4 Central Moments; 4.5 Conditional Expected Values; 4.6 Transformations of Random Variables; 4.6.1 Monotonically Increasing Functions; 4.6.2 Monotonically Decreasing Functions; 4.6.3 Nonmonotonic Functions; 4.7. Characteristic Functions; 4.8. Probability-Generating Functions 4.9 Moment-Generating Functions4.10 Evaluating Tail Probabilities; 4.11 Engineering Application-Scalar Quantization; 4.12 Engineering Application-Entropy and Source Coding; Exercises; Section 4.1: Expected Values of a Random Variable; Section 4.2: Expected Values of Functions of a Random Variable; Section 4.3: Moments; Section 4.4: Central Moments; Section 4.5: Conditional Expected Values; Section 4.6: Transformations of Random Variables; Section 4.7: Characteristic Functions; Section 4.8: Probability-Generating Functions; Section 4.9: Moment-Generating Functions Section 4.10: Evaluating Tail Probabilities |
| Record Nr. | UNINA-9910958181903321 |
|
Miller Scott L
|
||
| Waltham, Mass., : Elsevier, 2012 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Scaling, fractals and wavelets [[electronic resource] /] / edited by Patrice Abry, Paulo Gonçalves, Jacques Levy Vehel
| Scaling, fractals and wavelets [[electronic resource] /] / edited by Patrice Abry, Paulo Gonçalves, Jacques Levy Vehel |
| Pubbl/distr/stampa | London, : ISTE |
| Descrizione fisica | 1 online resource (506 p.) |
| Disciplina |
621.382/20151
621.38220151 |
| Altri autori (Persone) |
AbryPatrice
GonçalvesPaulo <1967-> Lévy VéhelJacques <1960-> |
| Collana | ISTE |
| Soggetto topico |
Signal processing - Mathematics
Fractals Wavelets (Mathematics) |
| ISBN |
1-282-16536-4
9786612165368 0-470-61156-1 0-470-39422-6 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Scaling, Fractals and Wavelets; Table of Contents; Preface; Chapter 1. Fractal and Multifractal Analysis in Signal Processing; 1.1. Introduction; 1.2. Dimensions of sets; 1.2.1. Minkowski-Bouligand dimension; 1.2.2. Packing dimension; 1.2.3. Covering dimension; 1.2.4. Methods for calculating dimensions; 1.3. Hölder exponents; 1.3.1. Hölder exponents related to a measure; 1.3.2. Theorems on set dimensions; 1.3.3. Hölder exponent related to a function; 1.3.4. Signal dimension theorem; 1.3.5. 2-microlocal analysis; 1.3.6. An example: analysis of stock market price; 1.4. Multifractal analysis
1.4.1. What is the purpose of multifractal analysis?1.4.2. First ingredient: local regularity measures; 1.4.3. Second ingredient: the size of point sets of the same regularity; 1.4.4. Practical calculation of spectra; 1.4.5. Refinements: analysis of the sequence of capacities, mutual analysis and multisingularity; 1.4.6. The multifractal spectra of certain simple signals; 1.4.7. Two applications; 1.4.7.1. Image segmentation; 1.4.7.2. Analysis of TCP traffic; 1.5. Bibliography; Chapter 2. Scale Invariance and Wavelets; 2.1. Introduction; 2.2. Models for scale invariance; 2.2.1. Intuition 2.2.2. Self-similarity2.2.3. Long-range dependence; 2.2.4. Local regularity; 2.2.5. Fractional Brownian motion: paradigm of scale invariance; 2.2.6. Beyond the paradigm of scale invariance; 2.3.Wavelet transform; 2.3.1. Continuous wavelet transform; 2.3.2. Discretewavelet transform; 2.4. Wavelet analysis of scale invariant processes; 2.4.1. Self-similarity; 2.4.2. Long-range dependence; 2.4.3. Local regularity; 2.4.4. Beyond second order; 2.5. Implementation: analysis, detection and estimation; 2.5.1. Estimation of the parameters of scale invariance 2.5.2. Emphasis on scaling laws and determination of the scaling range2.5.3. Robustness of the wavelet approach; 2.6. Conclusion; 2.7. Bibliography; Chapter 3. Wavelet Methods for Multifractal Analysis of Functions; 3.1. Introduction; 3.2. General points regarding multifractal functions; 3.2.1. Important definitions; 3.2.2. Wavelets and pointwise regularity; 3.2.3. Local oscillations; 3.2.4. Complements; 3.3. Random multifractal processes; 3.3.1. Lévy processes; 3.3.2. Burgers' equation and Brownian motion; 3.3.3. Random wavelet series; 3.4. Multifractal formalisms 3.4.1. Besov spaces and lacunarity3.4.2. Construction of formalisms; 3.5. Bounds of the spectrum; 3.5.1. Bounds according to the Besov domain; 3.5.2. Bounds deduced from histograms; 3.6. The grand-canonical multifractal formalism; 3.7. Bibliography; Chapter 4. Multifractal Scaling: General Theory and Approach by Wavelets; 4.1. Introduction and summary; 4.2. Singularity exponents; 4.2.1. Hölder continuity; 4.2.2. Scaling of wavelet coefficients; 4.2.3. Other scaling exponents; 4.3. Multifractal analysis; 4.3.1. Dimension based spectra; 4.3.2. Grain based spectra 4.3.3. Partition function and Legendre spectrum |
| Record Nr. | UNINA-9910139468203321 |
| London, : ISTE | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Scaling, fractals and wavelets [[electronic resource] /] / edited by Patrice Abry, Paulo Gonçalves, Jacques Levy Vehel
| Scaling, fractals and wavelets [[electronic resource] /] / edited by Patrice Abry, Paulo Gonçalves, Jacques Levy Vehel |
| Pubbl/distr/stampa | London, : ISTE |
| Descrizione fisica | 1 online resource (506 p.) |
| Disciplina |
621.382/20151
621.38220151 |
| Altri autori (Persone) |
AbryPatrice
GonçalvesPaulo <1967-> Lévy VéhelJacques <1960-> |
| Collana | ISTE |
| Soggetto topico |
Signal processing - Mathematics
Fractals Wavelets (Mathematics) |
| ISBN |
1-282-16536-4
9786612165368 0-470-61156-1 0-470-39422-6 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Scaling, Fractals and Wavelets; Table of Contents; Preface; Chapter 1. Fractal and Multifractal Analysis in Signal Processing; 1.1. Introduction; 1.2. Dimensions of sets; 1.2.1. Minkowski-Bouligand dimension; 1.2.2. Packing dimension; 1.2.3. Covering dimension; 1.2.4. Methods for calculating dimensions; 1.3. Hölder exponents; 1.3.1. Hölder exponents related to a measure; 1.3.2. Theorems on set dimensions; 1.3.3. Hölder exponent related to a function; 1.3.4. Signal dimension theorem; 1.3.5. 2-microlocal analysis; 1.3.6. An example: analysis of stock market price; 1.4. Multifractal analysis
1.4.1. What is the purpose of multifractal analysis?1.4.2. First ingredient: local regularity measures; 1.4.3. Second ingredient: the size of point sets of the same regularity; 1.4.4. Practical calculation of spectra; 1.4.5. Refinements: analysis of the sequence of capacities, mutual analysis and multisingularity; 1.4.6. The multifractal spectra of certain simple signals; 1.4.7. Two applications; 1.4.7.1. Image segmentation; 1.4.7.2. Analysis of TCP traffic; 1.5. Bibliography; Chapter 2. Scale Invariance and Wavelets; 2.1. Introduction; 2.2. Models for scale invariance; 2.2.1. Intuition 2.2.2. Self-similarity2.2.3. Long-range dependence; 2.2.4. Local regularity; 2.2.5. Fractional Brownian motion: paradigm of scale invariance; 2.2.6. Beyond the paradigm of scale invariance; 2.3.Wavelet transform; 2.3.1. Continuous wavelet transform; 2.3.2. Discretewavelet transform; 2.4. Wavelet analysis of scale invariant processes; 2.4.1. Self-similarity; 2.4.2. Long-range dependence; 2.4.3. Local regularity; 2.4.4. Beyond second order; 2.5. Implementation: analysis, detection and estimation; 2.5.1. Estimation of the parameters of scale invariance 2.5.2. Emphasis on scaling laws and determination of the scaling range2.5.3. Robustness of the wavelet approach; 2.6. Conclusion; 2.7. Bibliography; Chapter 3. Wavelet Methods for Multifractal Analysis of Functions; 3.1. Introduction; 3.2. General points regarding multifractal functions; 3.2.1. Important definitions; 3.2.2. Wavelets and pointwise regularity; 3.2.3. Local oscillations; 3.2.4. Complements; 3.3. Random multifractal processes; 3.3.1. Lévy processes; 3.3.2. Burgers' equation and Brownian motion; 3.3.3. Random wavelet series; 3.4. Multifractal formalisms 3.4.1. Besov spaces and lacunarity3.4.2. Construction of formalisms; 3.5. Bounds of the spectrum; 3.5.1. Bounds according to the Besov domain; 3.5.2. Bounds deduced from histograms; 3.6. The grand-canonical multifractal formalism; 3.7. Bibliography; Chapter 4. Multifractal Scaling: General Theory and Approach by Wavelets; 4.1. Introduction and summary; 4.2. Singularity exponents; 4.2.1. Hölder continuity; 4.2.2. Scaling of wavelet coefficients; 4.2.3. Other scaling exponents; 4.3. Multifractal analysis; 4.3.1. Dimension based spectra; 4.3.2. Grain based spectra 4.3.3. Partition function and Legendre spectrum |
| Record Nr. | UNINA-9910829972703321 |
| London, : ISTE | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Scaling, fractals and wavelets / / edited by Patrice Abry, Paulo Goncalves, Jacques Levy Vehel
| Scaling, fractals and wavelets / / edited by Patrice Abry, Paulo Goncalves, Jacques Levy Vehel |
| Pubbl/distr/stampa | London, : ISTE |
| Descrizione fisica | 1 online resource (506 p.) |
| Disciplina | 621.382/20151 |
| Altri autori (Persone) |
AbryPatrice
GoncalvesPaulo <1967-> Levy VehelJacques <1960-> |
| Collana | ISTE |
| Soggetto topico |
Signal processing - Mathematics
Fractals Wavelets (Mathematics) |
| ISBN |
1-282-16536-4
9786612165368 0-470-61156-1 0-470-39422-6 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Scaling, Fractals and Wavelets; Table of Contents; Preface; Chapter 1. Fractal and Multifractal Analysis in Signal Processing; 1.1. Introduction; 1.2. Dimensions of sets; 1.2.1. Minkowski-Bouligand dimension; 1.2.2. Packing dimension; 1.2.3. Covering dimension; 1.2.4. Methods for calculating dimensions; 1.3. Hölder exponents; 1.3.1. Hölder exponents related to a measure; 1.3.2. Theorems on set dimensions; 1.3.3. Hölder exponent related to a function; 1.3.4. Signal dimension theorem; 1.3.5. 2-microlocal analysis; 1.3.6. An example: analysis of stock market price; 1.4. Multifractal analysis
1.4.1. What is the purpose of multifractal analysis?1.4.2. First ingredient: local regularity measures; 1.4.3. Second ingredient: the size of point sets of the same regularity; 1.4.4. Practical calculation of spectra; 1.4.5. Refinements: analysis of the sequence of capacities, mutual analysis and multisingularity; 1.4.6. The multifractal spectra of certain simple signals; 1.4.7. Two applications; 1.4.7.1. Image segmentation; 1.4.7.2. Analysis of TCP traffic; 1.5. Bibliography; Chapter 2. Scale Invariance and Wavelets; 2.1. Introduction; 2.2. Models for scale invariance; 2.2.1. Intuition 2.2.2. Self-similarity2.2.3. Long-range dependence; 2.2.4. Local regularity; 2.2.5. Fractional Brownian motion: paradigm of scale invariance; 2.2.6. Beyond the paradigm of scale invariance; 2.3.Wavelet transform; 2.3.1. Continuous wavelet transform; 2.3.2. Discretewavelet transform; 2.4. Wavelet analysis of scale invariant processes; 2.4.1. Self-similarity; 2.4.2. Long-range dependence; 2.4.3. Local regularity; 2.4.4. Beyond second order; 2.5. Implementation: analysis, detection and estimation; 2.5.1. Estimation of the parameters of scale invariance 2.5.2. Emphasis on scaling laws and determination of the scaling range2.5.3. Robustness of the wavelet approach; 2.6. Conclusion; 2.7. Bibliography; Chapter 3. Wavelet Methods for Multifractal Analysis of Functions; 3.1. Introduction; 3.2. General points regarding multifractal functions; 3.2.1. Important definitions; 3.2.2. Wavelets and pointwise regularity; 3.2.3. Local oscillations; 3.2.4. Complements; 3.3. Random multifractal processes; 3.3.1. Lévy processes; 3.3.2. Burgers' equation and Brownian motion; 3.3.3. Random wavelet series; 3.4. Multifractal formalisms 3.4.1. Besov spaces and lacunarity3.4.2. Construction of formalisms; 3.5. Bounds of the spectrum; 3.5.1. Bounds according to the Besov domain; 3.5.2. Bounds deduced from histograms; 3.6. The grand-canonical multifractal formalism; 3.7. Bibliography; Chapter 4. Multifractal Scaling: General Theory and Approach by Wavelets; 4.1. Introduction and summary; 4.2. Singularity exponents; 4.2.1. Hölder continuity; 4.2.2. Scaling of wavelet coefficients; 4.2.3. Other scaling exponents; 4.3. Multifractal analysis; 4.3.1. Dimension based spectra; 4.3.2. Grain based spectra 4.3.3. Partition function and Legendre spectrum |
| Record Nr. | UNINA-9911019246103321 |
| London, : ISTE | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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