{"product_id":"mathematical-methods-in-modern-complexity-science-9783030794118","title":"Mathematical Methods in Modern Complexity Science","description":"\u003cp\u003e\u003c\/p\u003e\u003cblockquote\u003e\n\u003cbr\u003eThis book covers recent developments in nonlinear and complex systems, including information theory, relativistic chaotic dynamics, data analysis, solvability issues, and inverse problems. \u003c\/blockquote\u003e\u003cp\u003e\u003cstrong\u003eFormat\u003c\/strong\u003e: Hardback\u003cbr\u003e\u003cstrong\u003eLength\u003c\/strong\u003e: 197 pages\u003cbr\u003e\u003cstrong\u003ePublication date\u003c\/strong\u003e: 15 March 2022\u003cbr\u003e\u003cstrong\u003ePublisher\u003c\/strong\u003e: Springer Nature Switzerland AG\u003cbr\u003e\u003c\/p\u003e \u003cp\u003e\u003cbr\u003eThis comprehensive book delves into the latest advancements in nonlinear and complex systems, offering a wealth of theoretical developments and innovative techniques rooted in the nonlinear dynamical systems approach. It encompasses a wide range of topics, including information theory, relativistic chaotic dynamics, data analysis, relativistic chaotic dynamics, solvability issues in integro-differential equations, and inverse problems for parabolic differential equations, synchronization, and chaotic transient. By presenting these cutting-edge concepts, the book aims to provide a deeper understanding of complex systems and their behavior, paving the way for future research and applications in various fields.\u003cbr\u003e\u003cbr\u003eInformation theory plays a crucial role in understanding complex systems, as it provides a framework for encoding and transmitting data. In this chapter, we explore the principles of information theory and its applications in modeling and analyzing complex systems. We discuss topics such as entropy, mutual information, and channel capacity, which are essential for understanding the communication and information transfer processes in complex systems.\u003cbr\u003e\u003cbr\u003eRelativistic chaotic dynamics is a branch of mathematics that studies the behavior of systems that are governed by chaotic equations. Chaos is a state of unpredictable behavior that occurs when a system is sensitive to initial conditions, and it has been observed in a wide range of natural and artificial systems. In this chapter, we introduce the concept of relativistic chaotic dynamics and discuss its applications in modeling complex systems, such as celestial mechanics, biological systems, and social systems.\u003cbr\u003e\u003cbr\u003eData analysis is an essential tool for understanding complex systems, as it allows us to extract meaningful information from large datasets. In this chapter, we explore various data analysis techniques, such as statistical analysis, machine learning, and data visualization, and their applications in modeling and analyzing complex systems. We discuss topics such as regression analysis, cluster analysis, and dimensionality reduction, which are useful for identifying patterns and relationships in complex data.\u003cbr\u003e\u003cbr\u003eRelativistic chaotic dynamics is a branch of mathematics that studies the behavior of systems that are governed by chaotic equations. Chaos is a state of unpredictable behavior that occurs when a system is sensitive to initial conditions, and it has been observed in a wide range of natural and artificial systems. In this chapter, we introduce the concept of relativistic chaotic dynamics and discuss its applications in modeling complex systems, such as celestial mechanics, biological systems, and social systems.\u003cbr\u003e\u003cbr\u003eData analysis is an essential tool for understanding complex systems, as it allows us to extract meaningful information from large datasets. In this chapter, we explore various data analysis techniques, such as statistical analysis, machine learning, and data visualization, and their applications in modeling and analyzing complex systems. We discuss topics such as regression analysis, cluster analysis, and dimensionality reduction, which are useful for identifying patterns and relationships in complex data.\u003cbr\u003e\u003cbr\u003eSolvability issues in integro-differential equations are a fundamental problem in mathematical physics, as they arise in a wide range of applications, including celestial mechanics, chemical reactions, and biological systems. In this chapter, we introduce the concept of solvability issues in integro-differential equations and discuss various techniques for solving them, such as perturbation methods, numerical methods, and analytical methods. We also discuss the applications of these techniques in modeling complex systems.\u003cbr\u003e\u003cbr\u003eInverse problems for parabolic differential equations are a branch of mathematics that involves the solution of equations that arise in a wide range of applications, such as fluid dynamics, heat transfer, and electromagnetic fields. In this chapter, we introduce the concept of inverse problems for parabolic differential equations and discuss various techniques for solving them, such as regularization methods, optimization methods, and numerical methods. We also discuss the applications of these techniques in modeling complex systems.\u003cbr\u003e\u003cbr\u003eSynchronization and chaotic transient are two important phenomena that occur in complex systems. In this chapter, we introduce the concept of synchronization and discuss its applications in modeling and analyzing complex systems. We also discuss the concept of chaotic transient and its applications in understanding the behavior of complex systems.\u003cbr\u003e\u003cbr\u003eIn conclusion, this comprehensive book provides a comprehensive overview of the latest advancements in nonlinear and complex systems. It offers a wealth of theoretical developments and innovative techniques that can be used to model and understand complex behavior in nonlinear dynamical systems. By presenting these cutting-edge concepts, the book aims to provide a deeper understanding of complex systems and their behavior, paving the way\u003cbr\u003eway for future research and applications in various fields.\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003eWeight\u003c\/strong\u003e: 483g\u003cbr\u003e\u003cstrong\u003eDimension\u003c\/strong\u003e: 235 x 155 (mm)\u003cbr\u003e\u003cstrong\u003eISBN-13\u003c\/strong\u003e: 9783030794118\u003cbr\u003e \u003cstrong\u003eEdition number\u003c\/strong\u003e: 1st ed. 2022\u003c\/p\u003e","brand":"Shulph Ink","offers":[{"title":"Hardback","offer_id":44103119831290,"sku":"9783030794118","price":102.47,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0522\/4297\/2845\/products\/noImage_1_6c94cfed-8c2c-4b7f-a3e9-e3e932a8831b.jpg?v=1669553162","url":"https:\/\/shulphink.com\/products\/mathematical-methods-in-modern-complexity-science-9783030794118","provider":"Shulph Ink","version":"1.0","type":"link"}