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Cilia : Methods and protocols
Covers the latest advancements in the study of ciliary complexity. Protocols cover genomic, proteomic, imaging, and functional analysis of different ciliated tissues and their wide applicability in cilia biology. Chapters in this book primarily focus on methods to study multiciliated cells, and discuss topics such as SARS-CoV-2 infections of human primary nasal multiciliated epithelial cells; expansion microscopy of ciliary proteins; live-imaging centriole amplification in mouse brain multiciliated cells; biophysical properties of cilia motility; and mucociliary transport device construction. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, lists of the necessary materials and reagents, step-by-step, readily reproducible laboratory protocols, and tips on troubleshooting and avoiding known pitfalls.
Linear Systems, Signal Processing and Hypercomplex Analysis ; Chapman University, November 2017
includes contributions originating from a conference held at Chapman University during November 14-19, 2017. It presents original research by experts in signal processing, linear systems, operator theory, complex and hypercomplex analysis and related topics.
Kernel Methods for Machine Learning with Math and Python: 100 Exercises for Building Logic
Addresses the fundamentals of kernel methods for machine learning by considering relevant math problems and building Python programs. The book’s main features are as follows: Includes 100 exercises, which have been carefully selected and refined. As their solutions are provided in the main text, readers can solve all of the exercises by reading the book. / The mathematical premises of kernels are proven and the correct conclusions are provided, helping readers to understand the nature of kernels. / Source programs and running examples are presented to help readers acquire a deeper understanding of the mathematics used. / Once readers have a basic understanding of the functional analysis topics covered in Chapter 2, the applications are discussed in the subsequent chapters. Here, no prior knowledge of mathematics is assumed. / Considers both the kernel for reproducing kernel Hilbert space (RKHS) and the kernel for the Gaussian process; a clear distinction is made between the two.
Linear Functional Analysis
This introduction to the ideas and methods of linear functional analysis shows how familiar and useful concepts from finite-dimensional linear algebra can be extended or generalized to infinite-dimensional spaces. Aimed at advanced undergraduates in mathematics and physics, the book assumes a standard background of linear algebra, real analysis (including the theory of metric spaces), and Lebesgue integration, although an introductory chapter summarizes the requisite material. The initial chapters develop the theory of infinite-dimensional normed spaces, in particular Hilbert spaces, after which the emphasis shifts to studying operators between such spaces. Functional analysis has applications to a vast range of areas of mathematics; the final chapters discuss the particularly important areas of integral and differential equations.
Lie Groups : An Approach through Invariants and Representations
Lie groups has been an increasing area of focus and rich research since the middle of the 20th century. Procesi's masterful approach to Lie groups through invariants and representations gives the reader a comprehensive treatment of the classical groups along with an extensive introduction to a wide range of topics associated with Lie groups: symmetric functions, theory of algebraic forms, Lie algebras, tensor algebra and symmetry, semisimple Lie algebras, algebraic groups, group representations, invariants, Hilbert theory, and binary forms with fields ranging from pure algebra to functional analysis.
Chaos, Nonlinearity, Complexity : The Dynamical Paradigm of Nature
This carefully edited book presents a focused debate on the mathematics and physics of chaos, nonlinearity and complexity in nature. It explores the role of non-extensive statistical mechanics in non-equilibrium thermodynamics, and presents an overview of the strong nonlinearity of chaos and complexity in natural systems that draws on the relevant mathematics from topology, measure-theory, inverse and ill-posed problems, set-valued analysis, and nonlinear functional analysis. It presents a self-contained scientific theory of complexity and complex systems as the steady state of non-equilibrium systems, denoting a homeostatic dynamic equilibrium between stabilizing order and destabilizing disorder.
Biorthogonal Systems in Banach Spaces
The main theme of this book is the relation between the global structure of Banach spaces and the various types of generalized "coordinate systems" - or "bases" - they possess. In this book, the authors systematically investigate the concepts of Markushevich bases, fundamental systems, total systems and their variants.
Beyond partial differential equations : On linear and Quasi-Linear abstract hyperbolic evolution equations
The present volume is self-contained and introduces to the treatment of linear and nonlinear (quasi-linear) abstract evolution equations by methods from the theory of strongly continuous semigroups.
Applicazioni ed esercizi di modellistica numerica per problemi differenziali = Applications and exercises in numerical modeling for differential problems
Contains a collection of exercises related to typical topics in a course on analytical and numerical methods offered in a degree program in Engineering or Mathematics. Starting with exercises in functional analysis and approximation theory, the text develops problems related to the numerical resolution of elliptic, parabolic, and hyperbolic partial differential equations, scalar or vector, in one or more spatial dimensions. Pure diffusion and pure convection problems are therefore addressed, alongside diffusion-transport problems and problems in compressible and incompressible fluid dynamics. Particular emphasis is given to the finite element method for the spatial discretization of the problems considered, although exercises on the finite difference and finite volume methods are also included.
An Introduction to Operators on the Hardy-Hilbert Space
The subject of this book is operator theory on the Hardy space H2, also called the Hardy-Hilbert space. The goal is to provide an elementary and engaging introduction to this subject that will be readable by everyone who has understood introductory courses in complex analysis and in functional analysis.
An Introduction to Infinite-Dimensional Analysis
In this revised and extended version of his course notes from a 1-year course at Scuola Normale Superiore, Pisa, the author provides an introduction – for an audience knowing basic functional analysis and measure theory but not necessarily probability theory – to analysis in a separable Hilbert space of infinite dimension.Starting from the definition of Gaussian measures in Hilbert spaces, concepts such as the Cameron-Martin formula, Brownian motion and Wiener integral are introduced in a simple way. These concepts are then used to illustrate some basic stochastic dynamical systems (including dissipative nonlinearities) and Markov semi-groups, paying special attention to their long-time behavior: ergodicity, invariant measure. Here fundamental results like the theorems of Prokhorov, Von Neumann, Krylov-Bogoliubov and Khas'minski are proved. The last chapter is devoted to gradient systems and their asymptotic behavior.
Advanced Real Analysis
Basic Real Analysis and Advanced Real Analysis (available separately or together as a Set) systematically develop those concepts and tools in real analysis that are vital to every mathematician, whether pure or applied, aspiring or established. These works present a comprehensive treatment with a global view of the subject, emphasizing the connections between real analysis and other branches of mathematics.
