Learn IT - Books tags optimization

C in Depth

BPB Publications, 2019

In the third edition of the book C in depth , the authors explain the basics of the programming language while maintaining the integrity and clarity of the programs. The book can be utilized by both beginners and advanced level programmers as a self-evaluation and learning source. There are more than 310 programs with explanations to illustrate...

Expert Python Programming: Become a master in Python by learning coding best practices and advanced programming concepts in Python 3.7, 3rd Edition

Packt Publishing, 2019

Refine your Python programming skills and build professional grade applications with this comprehensive guide

Key Features

Create manageable code that can run in various environments with different sets of dependencies

Implement effective Python data structures and...

Machine Learning and AI for Healthcare: Big Data for Improved Health Outcomes

Apress, 2019

Explore the theory and practical applications of artificial intelligence (AI) and machine learning in healthcare. This book offers a guided tour of machine learning algorithms, architecture design, and applications of learning in healthcare and big data challenges.

You’ll discover the...

Mastering Go: Create Golang production applications using network libraries, concurrency, and advanced Go data structures

Packt Publishing, 2018

Exploring the major features and packages of Go, along with its types and data-structures, enabling the reader to write threadsafe, concurrent cloud, and network applications

Key Features

Not your typical introduction to the Golang programming language

Exploring Golang...

Hands-On GPU Programming with Python and CUDA: Explore high-performance parallel computing with CUDA

Packt Publishing, 2018

Build GPU-accelerated high performing applications with Python 2.7, CUDA 9, and open source libraries such as PyCUDA and scikit-cuda. We recommend the use of Python 2.7 as this version has stable support across all libraries used in this book.

Key Features

Get to grips with GPU programming...

Applied Deep Learning: A Case-Based Approach to Understanding Deep Neural Networks

Apress, 2018

Work with advanced topics in deep learning, such as optimization algorithms, hyper-parameter tuning, dropout, and error analysis as well as strategies to address typical problems encountered when training deep neural networks. You’ll begin by studying the activation functions mostly with a single neuron (ReLu, sigmoid, and...

Proportionate-type Normalized Least Mean Square Algorithms

John Wiley & Sons, 2013

The topic of this book is proportionate-type normalized least mean squares (PtNLMS) adaptive filtering algorithms, which attempt to estimate an unknown impulse response by adaptively giving gains proportionate to an estimate of the impulse response and the current measured error. These algorithms offer low computational complexity...

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...

Electronic Design Automation of Analog ICs combining Gradient Models with Multi-Objective Evolutionary Algorithms (SpringerBriefs in Applied Sciences and Technology)

Springer, 2013

This book applies to the scientific area of electronic design automation (EDA) and addresses the automatic sizing of analog integrated circuits (ICs). Particularly, this book presents an approach to enhance a state-of-the-art layout-aware circuit-level optimizer (GENOM-POF), by embedding statistical knowledge from an automatically generated...

Music-Inspired Harmony Search Algorithm: Theory and Applications (Studies in Computational Intelligence)

Springer, 2009

Calculus has been used in solving many scientific and engineering problems. For optimization problems, however, the differential calculus technique sometimes has a drawback when the objective function is step-wise, discontinuous, or multi-modal, or when decision variables are discrete rather than continuous. Thus, researchers have...

Simulation and Optimization in Finance: Modeling with MATLAB, @Risk, or VBA

John Wiley & Sons, 2010

An introduction to the theory and practice of financial simulation and optimization

In recent years, there has been a notable increase in the use of simulation and optimization methods in the financial industry. Applications include portfolio allocation, risk management, pricing, and capital budgeting under uncertainty.

...

Advanced Control of Industrial Processes: Structures and Algorithms (Advances in Industrial Control)

Springer, 2006

This book presents the concepts and algorithms of advanced industrial process control and on-line optimization within the framework of a multilayer structure. It describes the interaction of three separate layers of process control: direct control, set-point control, and economic optimization. The book features illustrations of the...

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