Learn IT - Books tags algorithm

Genetic Programming Theory and Practice X (Genetic and Evolutionary Computation)

Springer, 2013

These contributions, written by the foremost international researchers and practitioners of Genetic Programming (GP), explore the synergy between theoretical and empirical results on real-world problems, producing a comprehensive view of the state of the art in GP.

Topics in this volume include: evolutionary constraints,...

Introduction to the Design and Analysis of Algorithms (3rd Edition)

Pearson Education, 2011

Based on a new classification of algorithm design techniques and a clear delineation of analysis methods, Introduction to the Design and Analysis of Algorithms presents the subject in a coherent and innovative manner. Written in a student-friendly style, the book emphasizes the understanding of ideas over excessively formal...

Algorithm Design: Foundations, Analysis and Internet Examples

John Wiley & Sons, 2001

This book is designed to provide a comprehensive introduction to the design and analysis of computer algorithms and data structures. In terms M the computer science and computer engineering curricula, we have written this book to be primarily focused on the Junior-Senior level Algorithms (CS7) course, which is taught as a...

An Introduction to Quantum Computing Algorithms

Birkhauser, 2001

In 1994 Peter Shor [65] published a factoring algorithm for a quantum computer that finds the prime factors of a composite integer N more efficiently than is possible with the known algorithms for a classical com puter. Since the difficulty of the factoring problem is crucial for the se curity of a public key encryption system,...

Spatio-temporal Networks: Modeling and Algorithms (SpringerBriefs in Computer Science)

Springer, 2012

Spatio-temporal networks (STN)are spatial networks whose topology and/or attributes change with time. These are encountered in many critical areas of everyday life such as transportation networks, electric power distribution grids, and social networks of mobile users. STN modeling and computations raise significant challenges. The model must...

A VLSI Architecture for Concurrent Data Structures (The Springer International Series in Engineering and Computer Science)

Springer, 2011

Concurrent data structures simplify the development of concurrent programs by encapsulating commonly used mechanisms for synchronization and commu nication into data structures. This thesis develops a notation for describing concurrent data structures, presents examples of concurrent data structures, and describes an architecture to support...

Optimization Algorithms for Networks and Graphs

CRC Press, 1992

A revised and expanded advanced-undergraduate/graduate text (first ed., 1978) about optimization algorithms for problems that can be formulated on graphs and networks. This edition provides many new applications and algorithms while maintaining the classic foundations on which contemporary algorithm...

Algorithms in C, Parts 1-4: Fundamentals, Data Structures, Sorting, Searching (3rd Edition) (Pts. 1-4)

Addison Wesley, 1997

Robert Sedgewick has thoroughly rewritten and substantially expanded his popular work to provide current and comprehensive coverage of important algorithms and data structures. Many new algorithms are presented, and the explanations of each...

Modular Algorithms in Symbolic Summation and Symbolic Integration (Lecture Notes in Computer Science)

Springer, 2005

This work brings together two streams in computer algebra: symbolic integration and summation on the one hand, and fast algorithmics on the other hand. In many algorithmically oriented areas of computer science, theanalysisof- gorithms–placedintothe limelightbyDonKnuth’stalkat the 1970ICM –provides a crystal-clear criterion for...

Mathematical Methods and Algorithms for Signal Processing

Pearson Education, 1999

Mathematical Methods and Algorithms for Signal Processing tackles the challenge of providing readers and practitioners with the broad tools of mathematics employed in modern signal processing. Building from an assumed background in signals and stochastic processes, the book provides a solid foundation in analysis, linear...

Machine Learning Using R: With Time Series and Industry-Based Use Cases in R

Apress, 2018

Examine the latest technological advancements in building a scalable machine-learning model with big data using R. This second edition shows you how to work with a machine-learning algorithm and use it to build a ML model from raw data. You will see how to use R programming with TensorFlow, thus avoiding the effort of learning Python...

Blockchain for Business 2019: A user-friendly introduction to blockchain technology and its business applications

Packt Publishing, 2019

Your one-stop guide to blockchain technology and its business applications

Key Features

Assimilate blockchain services such as Ethereum and Hyperledger to transform industrial applications

Know in and out of blockchain technology to understand various business use...

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