Learn IT - Books tags linear

Numerical Methods for Chemical Engineering: Applications in MATLAB

Cambridge University Press, 2006

Suitable for a first year graduate course, this textbook unites the applications of numerical mathematics and scientific computing to the practice of chemical engineering. Written in a pedagogic style, the book describes basic linear and nonlinear algebric systems all the way through to stochastic methods, Bayesian statistics and parameter...

Linear Programming and Algorithms for Communication Networks: A Practical Guide to Network Design, Control, and Management

CRC Press, 2012

Explaining how to apply to mathematical programming to network design and control, Linear Programming and Algorithms for Communication Networks: A Practical Guide to Network Design, Control, and Management fills the gap between mathematical programming theory and its implementation in communication networks. From the...

Hands-On Reinforcement Learning with Python: Master reinforcement and deep reinforcement learning using OpenAI Gym and TensorFlow

Packt Publishing, 2018

A hands-on guide enriched with examples to master deep reinforcement learning algorithms with Python

Key Features

Enter the world of artificial intelligence using the power of Python

An example-rich guide to master various RL and DRL algorithms

Explore...

Advances in Nonlinear Signal and Image Processing (EURASIP Book Series on Signal Processing and Communications)

Hindawi Publishing, 2006

The interest in nonlinear methods in signal processing is steadily increasing, since nowadays the advances in computational capacities make it possible to implement sophisticated nonlinear processing techniques which in turn allow remarkable improvements with respect to standard and well-consolidated linear processing approaches.

The aim of the...

Instant Boris Effects (VASST Instant)

CMP Books, 2004

Boris plug-in applications, including Graffiti, FX, and Red, permit video editors to add titling, effects, compositing, and 3D capabilities to their nonlinear editing (NLE) systems. Documentation and training materials have been notoriously lacking for these applications. Instant Boris Effects is a complete guide for novice and intermediate users...

Classical Mechanics with Mathematica® (Modeling and Simulation in Science, Engineering and Technology)

Birkhauser, 2012

This textbook takes a broad yet thorough approach to mechanics, aimed at bridging the gap between classical analytic and modern differential geometric approaches to the subject.â Developed by the author from 35 years of teaching experience, the presentation is designed to give students an overview of the many...

Probability and Algorithms

National Academy Press, 1992

Some of the hardest computational problems have been successfully attacked through the use of probabilistic algorithms, which have an element of randomness to them. Concepts from the field of probability are also increasingly useful in analyzing the performance of algorithms, broadening our understanding beyond that provided by the...

Handbook of Discrete and Combinatorial Mathematics

CRC Press, 1999

I like the book's format. There are glossaries at the beginning of each chapter. Each subsection begins with definitions and goes on to facts, then algorithms (boxed and in pseudo -code), lists of mathematical objects, illuminating pictures, examples, lists of applications, and, finally, bibliography and web sources. This handbook will appeal both...

Handbook of Differential Equations: Stationary Partial Differential Equations, Volume 6

Elsevier Limited, 2008

This is a survey on elliptic boundary value problems on varying domains and tools needed for that. Such problems arise in numerical analysis, in shape optimisation problems and in the investigation of the solution structure of nonlinear elliptic equations. The methods are also useful to obtain certain results for equations on non-smooth...

Advanced R Statistical Programming and Data Models: Analysis, Machine Learning, and Visualization

Apress, 2019

Carry out a variety of advanced statistical analyses including generalized additive models, mixed effects models, multiple imputation, machine learning, and missing data techniques using R. Each chapter starts with conceptual background information about the techniques, includes multiple examples using R to achieve results, and...

Machine Learning Methods in the Environmental Sciences: Neural Networks and Kernels

Cambridge University Press, 2009

Machine learning is a major subfield in computational intelligence (also called artificial intelligence). Its main objective is to use computational methods to extract information from data. Neural network methods, generally regarded as forming the first wave of breakthrough in machine learning, became popular in the late 1980s, while kernel...

Handbook of Time Series Analysis, Signal Processing, and Dynamics

Academic Press, 1999

It is hoped that this book will serve both as a text in time-series analysis and signal processing and as a reference book for research workers and practitioners. Timeseries analysis and signal processing are two subjects which ought to be treated as one; and they are the concern of a wide range of applied disciplines including statistics,...

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