De Somno Et Insomniis. La Vida Monástica a Través del Lecho y los Procesos del S González Dávila, María Angélica; Ríos Espinosa, María Cristi Bonilla Artigas Editores |
Sobre la Animalidad (Y Otros Textos Afines de Política Contemporánea) Villegas Contreras, Armando Bonilla Artigas Editores |
Antropologías Feministas en México: Epistemologías, Éticas, Prácticas y Miradas Berrio, Castañeda, Goldsmith, Ruiz, Salas y Valladares Bonilla Artigas Editores |
Experiencias de Bioconstrucción: Conceptos Generales y Visiones Desde México Caballero Cervantes, Alejandra; Luis Fernando Guerrero Baca Bonilla Artigas Editores |
¿Cómo Comprender Lo Social Para Colaborar en Su Cambio? Diego Quintana, Roberto Bonilla Artigas Editores |
Libertades Universitarias Bajo la Monarquía Hispánica, Las: Salamanca, México Y Pavón Romero, Armando; Blasco Gil, Yolanda Bonilla Artigas Editores |
Título: Linear Algebra And Probability For Computer Science Applications | ||
Autor: Davis, Ernest | Precio: $960.00 | |
Editorial: Crc Press | Año: 2012 | |
Tema: Algebra, Novela Mexicana | Edición: 1ª | |
Sinopsis | ISBN: 9781466501553 | |
Based on the author's course at NYU, Linear Algebra and Probability for Computer Science Applications gives an introduction to two mathematical fields that are fundamental in many areas of computer science. The course and the text are addressed to students with a very weak mathematical background. Most of the chapters discuss relevant MATLAB® functions and features and give sample assignments in MATLAB; the author's website provides the MATLAB code from the book.
After an introductory chapter on MATLAB, the text is divided into two sections. The section on linear algebra gives an introduction to the theory of vectors, matrices, and linear transformations over the reals. It includes an extensive discussion on Gaussian elimination, geometric applications, and change of basis. It also introduces the issues of numerical stability and round-off error, the discrete Fourier transform, and singular value decomposition. The section on probability presents an introduction to the basic theory of probability and numerical random variables; later chapters discuss Markov models, Monte Carlo methods, information theory, and basic statistical techniques. The focus throughout is on topics and examples that are particularly relevant to computer science applications; for example, there is an extensive discussion on the use of hidden Markov models for tagging text and a discussion of the Zipf (inverse power law) distribution. Examples and Programming Assignments The examples and programming assignments focus on computer science applications. The applications covered are drawn from a range of computer science areas, including computer graphics, computer vision, robotics, natural language processing, web search, machine learning, statistical analysis, game playing, graph theory, scientific computing, decision theory, coding, cryptography, network analysis, data compression, and signal processing. |