Title
Dynamic Mode Decomposition: Datadriven Modeling Of Complex Systems
Sold by Ergodebooks, an authorized reseller.
Returns accepted within 30 days | support@ergodebooks.com
Shipping Information
- Free Standard Shipping — United States only
- Processing Time: 1–3 business days
- Estimated Delivery: 3–5 business days after dispatch
- Double-boxed, fully insured & discreetly packaged
- Tracking number sent via email once dispatched
- Orders over $250 require signature upon delivery. Taxes calculated at checkout.
Returns & Refund
Returns accepted within 30 days of delivery.
Damaged or Defective Item
Free return shipping + replacement or full refund
Wrong Item Received
Free return shipping + replacement or full refund
Change of Mind
Return shipping at customer's expense · 25% restocking fee applies
Payment Option
Datadriven Dynamical Systems Is A Burgeoning Fieldit Connects How Measurements Of Nonlinear Dynamical Systems And/Or Complex Systems Can Be Used With Wellestablished Methods In Dynamical Systems Theory. This Is A Critically Important New Direction Because The Governing Equations Of Many Problems Under Consideration By Practitioners In Various Scientific Fields Are Not Typically Known. Thus, Using Data Alone To Help Derive, In An Optimal Sense, The Best Dynamical System Representation Of A Given Application Allows For Important New Insights. The Recently Developed Dynamic Mode Decomposition (Dmd) Is An Innovative Tool For Integrating Data With Dynamical Systems Theory. The Dmd Has Deep Connections With Traditional Dynamical Systems Theory And Many Recent Innovations In Compressed Sensing And Machine Learning.Dynamic Mode Decomposition: Datadriven Modeling Of Complex Systems, The First Book To Address The Dmd Algorithm, Presents A Pedagogical And Comprehensive Approach To All Aspects Of Dmd Currently Developed Or Under Development; Blends Theoretical Development, Example Codes, And Applications To Showcase The Theory And Its Many Innovations And Uses; Highlights The Numerous Innovations Around The Dmd Algorithm And Demonstrates Its Efficacy Using Example Problems From Engineering And The Physical And Biological Sciences; And Provides Extensive Matlab Code, Data For Intuitive Examples Of Key Methods, And Graphical Presentations.Audience: The Core Audience For This Book Is Engineers And Applied Mathematicians Working In The Physical And Biological Sciences. It Can Be Used In Courses That Integrate Data Analysis With Dynamical Systems.Contents: Contents; Preface; Notations; Acronyms; Chapter 1: Dynamic Mode Decomposition: An Introduction; Chapter 2: Fluid Dynamics; Chapter 3: Koopman Analysis; Chapter 4: Video Processing; Chapter 5: Multiresolution Dmd; Chapter 6: Dmd With Control; Chapter 7: Delay Coordinates, Era, And Hidden Markov Models; Chapter 8: Noise And Power; Chapter 9: Sparsity And Dmd; Chapter 10: Dmd On Nonlinear Observables; Chapter 11: Epidemiology; Chapter 12: Neuroscience; Chapter 13: Financial Trading; Glossary; Bibliography; Index.
⚠️ WARNING (California Proposition 65):
This product may contain chemicals known to the State of California to cause cancer, birth defects, or other reproductive harm.
For more information, please visit www.P65Warnings.ca.gov.
- Q: What is the page count of this book? A: This book has two hundred fifty pages. It provides a comprehensive exploration of dynamic mode decomposition and its applications.
- Q: What is the binding type of this book? A: This book is published in a paperback binding. This makes it lightweight and easy to handle for reading and note-taking.
- Q: Who is the author of this book? A: The author of this book is J. Nathan Kutz. He is recognized for his expertise in dynamical systems and data-driven modeling.
- Q: What topics are covered in this book? A: This book covers topics such as fluid dynamics, video processing, and neuroscience. It provides insights into various applications of dynamic mode decomposition.
- Q: Is this book suitable for beginners? A: Yes, this book is suitable for beginners. It offers a pedagogical approach that introduces the DMD algorithm comprehensively.
- Q: Can this book be used in academic courses? A: Yes, this book can be used in academic courses. It integrates data analysis with dynamical systems, making it ideal for engineering and mathematics courses.
- Q: How should I store this book? A: Store this book in a cool, dry place. Keep it upright on a shelf to prevent bending or damage to the spine.
- Q: Is this book safe for all ages? A: Yes, this book is appropriate for all ages. It is designed for readers interested in engineering and applied mathematics.
- Q: How do I clean this book if needed? A: To clean this book, gently wipe the cover with a soft cloth. Avoid using liquids that could damage the pages.
- Q: What if the book arrives damaged? A: If the book arrives damaged, contact customer support for a replacement. Most sellers have return policies for such situations.
- Q: Is this book focused on theory or practical applications? A: This book focuses on both theory and practical applications. It blends theoretical development with example codes and real-world applications.
- Q: Are there any code examples included in the book? A: Yes, the book includes extensive MATLAB code examples. These examples illustrate key methods for applying dynamic mode decomposition.
- Q: What is the target audience for this book? A: The target audience includes engineers and applied mathematicians. It is particularly useful for those in the physical and biological sciences.
- Q: Does this book explain complex systems? A: Yes, this book explains complex systems. It connects data-driven approaches with established methods in dynamical systems theory.
- Q: What kind of innovations does this book highlight? A: The book highlights innovations around the dynamic mode decomposition algorithm. It demonstrates efficacy through example problems in various fields.
- Q: Is there a glossary included in the book? A: Yes, the book includes a glossary. This helps readers understand key terms related to dynamic mode decomposition and its applications.