Master the practical aspects of implementing deep learning solutions with PyTorch, using a hands-on approach to understanding both theory and practice. This updated edition will prepare you for applying deep learning to real world problems with a sound theoretical foundation and practical know-how with PyTorch, a platform developed by...

The theory of distributions has numerous applications and is extensively used in mathematics, physics and engineering. There is however relatively little elementary expository literature on distribution theory. This book is intended as an introduction. Starting with the elementary theory of distributions, it proceeds to convolution products...

This book introduces the use of the distinct element method (DEM) in modeling crowd behavior and simulating evacuation processes. Focusing on the mathematical computation of the uncertain behavior of evacuees, which is switching action behavior, it subsequently reproduces the crowd evacuation process under several conjectural...

If you understand basic mathematics and know how to program with Python, you’re ready to dive into signal processing. While most resources start with theory to teach this complex subject, this practical book introduces techniques by showing you how they’re applied in the real world. In the first chapter alone,...

For a comprehensive, easy-to-swallow guide to OpenCL Programming, this book is out on its own. That's because it teaches through examples and covers everything from parallel sorting to optimization in simple stages.

Overview

Learn about all of the OpenCL Architecture and major APIs.

The book is a valuable research tool-kit for innovators, amateur & professionals alike. Additionally, College & University faculties on Engineering, who organize yearly workshops internationally will find hundreds of novel themes to choose from. Some teachers might just secretly buy this book to introduce out-of-box brain-teasers in...

A thorough guide to the classical and contemporary mathematical methods of modern signal and image processing

Discrete Fourier Analysis and Wavelets presents a thorough introduction to the mathematical foundations of signal and image processing. Key concepts and applications are addressed in a thought-provoking...

This text presents the fundamentals of circuit analysis in a way suitable for first and second year undergraduate courses in electronic or electrical engineering. It is very much a ‘theme text’ and not a work book. The author is at pains to follow the logical thread of the subject, showing that the development of topics, one from...

This book presents deep learning techniques, concepts, and algorithms to classify and analyze big data. Further, it offers an introductory level understanding of the new programming languages and tools used to analyze big data in real-time, such as Hadoop, SPARK, and GRAPHX. Big data analytics using traditional techniques...

The main goal of this graduate-level text is to provide a language for understanding, unifying, and implementing a wide variety of algorithms for digital signal processing -- in particular, to provide rules and procedures that can simplify or even automate the task of writing code for the newest parallel and vector machines. It thus bridges...

The Langlands Programme is one of the most important areas in modern pure mathematics. The importance of this volume lies in its potential to recast many aspects of the programme in an entirely new context. For example, the morphisms in the monomial category of a locally p–adic Lie group have a distributional description, due...

Get started with MATLAB for deep learning and AI with this in-depth primer. In this book, you start with machine learning fundamentals, then move on to neural networks, deep learning, and then convolutional neural networks. In a blend of fundamentals and applications, MATLAB Deep Learning employs MATLAB as the underlying programming...