Tag: Linear

Free Download Spatial Linear Models for Environmental Data
by Dale L. Zimmerman
English | 2024 | ISBN: 036718334X | 400 pages | True PDF | 130.77 MB

Free Download Linear Regression With Python: A Tutorial Introduction to the Mathematics of Regression Analysis by James V. Stone
English | January 13, 2022 | ISBN: 191627918X | True PDF | 138 pages | 3.6 MB
Linear regression is the workhorse of data analysis. It is the first step, and often the only step, in fitting a simple model to data. This brief book explains the essential mathematics required to understand and apply regression analysis.

Free Download Generalized Linear Mixed Models: Walter W. Stroup, Marina Ptukhina and Julie Garai
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English | 2024 | ISBN: 1498755569 | 671 pages | True PDF | 144.49 MB

Free Download Recent Stability Issues for Linear Dynamical Systems
English | 2024 | ISBN: 3031713257 | 187 Pages | PDF EPUB (True) | 15 MB
This book concerns matrix nearness problems in the framework of spectral optimization. It addresses some current research directions in spectral-based stability studies for differential equations, with material on ordinary differential equations (ODEs), differential algebraic equations and dynamical systems. Here, ‘stability’ is interpreted in a broad sense which covers the need to develop stable and reliable algorithms preserving some qualitative properties of the computed solutions, methodologies which are helpful to assess the onset of potential instabilities or loss of robustness, and tools to determine the asymptotic properties of the solution or its discretization.

Free Download Michael Filimowicz, "Foundations in Sound Design for Linear Media: A Multidisciplinary Approach"
English | ISBN: 1138093963 | 2019 | 418 pages | PDF | 20 MB
This volume provides a comprehensive introduction to foundational topics in sound design for linear media, such as listening and recording; audio postproduction; key musical concepts and forms such as harmony, conceptual sound design, electronica, soundscape, and electroacoustic composition; the audio commons; and sound’s ontology and phenomenology.

Free Download Introduction to Linear Elasticity By Phillip L. Gould (auth.)
2013 | 346 Pages | ISBN: 1461448328 | PDF | 4 MB
Introduction to Linear Elasticity, 3rd Edition provides an applications-oriented grounding in the tensor-based theory of elasticity for students in mechanical, civil, aeronautical, biomedical engineering, as well as materials and earth science. The book is distinct from the traditional text aimed at graduate students in solid mechanics by introducing its subject at a level appropriate for advanced undergraduate and beginning graduate students. The author’s presentation allows students to apply the basic notions of stress analysis and move on to advanced work in continuum mechanics, plasticity, plate and shell theory, composite materials, and finite method analysis.

Free Download Before Machine Learning Volume 1 – Linear Algebra: The Fundamental Mathematics for Data Science and Artificial Intelligence by Jorge Brasil
English | May 18, 2023 | ISBN: 9798393173104 | True PDF | 151 pages | 4.8 MB
Has the abstract nature of linear algebra ever left you overwhelmed? Do you yearn to unlock the essence of machine learning but are bogged down by the intricacy of the mathematics? Dive into a realm where linear algebra unfolds not just as numerical operations, but as a powerful story. A story intertwined with the magic of machine learning, making sense of data, and unraveling algorithms that power tomorrow.

Free Download Linear and Graphical Models: for the Multivariate Complex Normal Distribution By H. H. Andersen, M. Højbjerre, D. Sørensen, P. S. Eriksen (auth.)
1995 | 183 Pages | ISBN: 0387945210 | PDF | 4 MB
In the last decade, graphical models have become increasingly popular as a statistical tool. This book is the first which provides an account of graphical models for multivariate complex normal distributions. Beginning with an introduction to the multivariate complex normal distribution, the authors develop the marginal and conditional distributions of random vectors and matrices. Then they introduce complex MANOVA models and parameter estimation and hypothesis testing for these models. After introducing undirected graphs, they then develop the theory of complex normal graphical models including the maximum likelihood estimation of the concentration matrix and hypothesis testing of conditional independence.

Free Download Linear Algebra for Signal Processing By P. Comon (auth.), Adam Bojanczyk, George Cybenko (eds.)
1995 | 184 Pages | ISBN: 1461287030 | PDF | 5 MB
Signal processing applications have burgeoned in the past decade. During the same time, signal processing techniques have matured rapidly and now include tools from many areas of mathematics, computer science, physics, and engineering. This trend will continue as many new signal processing applications are opening up in consumer products and communications systems. In particular, signal processing has been making increasingly sophisticated use of linear algebra on both theoretical and algorithmic fronts. This volume gives particular emphasis to exposing broader contexts of the signal processing problems so that the impact of algorithms and hardware can be better understood; it brings together the writings of signal processing engineers, computer engineers, and applied linear algebraists in an exchange of problems, theories, and techniques. This volume will be of interest to both applied mathematicians and engineers.

Free Download Distortion Theorems in Relation to Linear Integral Operators By Yûsaku Komatu (auth.)
1996 | 312 Pages | ISBN: 9401062811 | PDF | 10 MB
The present monograph consists of two parts. Before Part I, a chapter of introduction is supplemented, where an overview of the whole volume is given for reader’s convenience. The former part is devoted mainly to expose linear inte gral operators introduced by the author. Several properties of the operators are established, and specializations as well as generalizations are attempted variously in order to make use them in the latter part. As compared with the former part, the latter part is de voted mainly to develop several kinds of distortions under actions of integral operators for various familiar function also absolute modulus. real part. range. length and area. an gular derivative, etc. Besides them, distortions on the class of univalent functions and its subclasses, Caratheodory class as well as distortions by a differential operator are dealt with. Related differential operators play also active roles. Many illustrative examples will be inserted in order to help understanding of the general statements. The basic materials in this monograph are taken from a series of researches performed by the author himself chiefly in the past two decades. While the themes of the papers pub lished hitherto are necessarily not arranged chronologically Preface viii and systematically, the author makes here an effort to ar range them as ,orderly as possible. In attaching the import ance of the self-containedness to the book, some of unfamil iar subjects will also be inserted and, moreover, be wholly accompanied by their respective proofs, though unrelated they may be.