الصفحة 1
الصفحة 1
Numerical Methods Using Java : For Data Science, Analysis, and Engineering
Covers a wide range of topics, including chapters on linear algebra, root finding, curve fitting, differentiation and integration, solving differential equations, random numbers and simulation, a whole suite of unconstrained and constrained optimization algorithms, statistics, regression and time series analysis. The mathematical concepts behind the algorithms are clearly explained, with plenty of code examples and illustrations to help even beginners get started. You will: Program in Java using a high-performance numerical library / Learn the mathematics for a wide range of numerical computing algorithms / Convert ideas and equations into code / Put together algorithms/ and classes to build your own engineering solution / Build solvers for industrial optimization problems / Do data analysis using basic and advanced statistics
Guide to Deep Learning Basics : Logical, Historical and Philosophical Perspectives
This stimulating text/reference presents a philosophical exploration of the conceptual foundations of deep learning, presenting enlightening perspectives that encompass such diverse disciplines as computer science, mathematics, logic, psychology, and cognitive science. The text also highlights select topics from the fascinating history of this exciting field, including the pioneering work of Rudolf Carnap, Warren McCulloch, Walter Pitts, Bulcsú László, and Geoffrey Hinton.
Dynamic characterisation of analogue-to-digital converters
Dynamic Characterisation of Analogue-to-Digital Converters presents a state of the art overview of the methods and procedures employed for characterising ADCs’ dynamic performance behaviour using sinusoidal stimuli. The three classical methods – histogram, sine wave fitting, and spectral analysis – are thoroughly described, and new approaches are proposed to circumvent some of their limitations
Computer Vision – ACCV 2007 ; 8th Asian Conference on Computer Vision, Tokyo, Japan, November 18-22, 2007, Proceedings, Part II
Contains sections on shape and texture, fitting, calbration, detection, image and video processing, applications, face and gesture, tracking, camera networks, and face/gesture/action detection and recognition. This book also covers learning, motion and tracking, retrival and search, and human pose estimation.
Computer Vision – ACCV 2007 ; 8th Asian Conference on Computer Vision, Tokyo, Japan, November 18-22, 2007, Proceedings, Part I
Contains sections on shape and texture, fitting, calbration, detection, image and video processing, applications, face and gesture, tracking, camera networks, and face/gesture/action detection and recognition. This book also covers learning, motion and tracking, retrival and search, and human pose estimation.
Advances in Mass Data Analysis of Images and Signals in Medicine, Biotechnology, Chemistry and Food Industry ; 3rd International Conference, MDA 2008 Leipzig, Germany, July 14, 2008 Proceedings
Presents the broad and growing scientific evidence linking mass data analysis with challenging problems in medicine, biotechnology and chemistry.
A First Course in Statistical Inference
Offers a modern and accessible introduction to Statistical Inference, the science of inferring key information from data. Aimed at beginning undergraduate students in mathematics, it presents the concepts underpinning frequentist statistical theory. Written in a conversational and informal style, this concise text concentrates on ideas and concepts, with key theorems stated and proved. Detailed worked examples are included and each chapter ends with a set of exercises, with full solutions given at the back of the book. Examples using R are provided throughout the book, with a brief guide to the software included. Topics covered in the book include: sampling distributions, properties of estimators, confidence intervals, hypothesis testing, ANOVA, and fitting a straight line to paired data.
