Algorithms and data structures

Real-time or applied digital signal processing courses are offered as follow-ups to conventional or theory-oriented digital signal processing courses in many engineering programs for the purpose of teaching students the technical know-how for putting signal processing algorithms or theory into practical use.

Real-time or applied digital signal processing courses are offered as follow-ups to conventional or theory-oriented digital signal processing courses in many engineering programs for the purpose of teaching students the technical know-how for putting signal processing algorithms or theory into practical use.

The adaptive configuration of nodes in a sensor network has the potential to improve sequential estimation performance by intelligently allocating limited sensor network resources.

The ubiquitous challenge of learning and decision-making from rank data arises in situations where intelligent systems collect preference and behavior data from humans, learn from the data, and then use the data to help humans make efficient, effective, and timely decisions.

The real-world data, though massive, is largely unstructured, in the form of natural-language text.

Diffusion processes in large networks have been used to model many real-world phenomena, including how rumors spread on the Internet, epidemics among human beings, emotional contagion through social networks, and even gene regulatory processes.

The wide diffusion of 3D printing technologies continuously calls for effective solutions for designing and fabricating objects of increasing complexity.

Computers and computer networks are one of the most incredible inventions of the 20th century, having an ever-expanding role in our daily lives by enabling complex human activities in areas such as entertainment, education, and commerce.

Automatic content generation is the production of content for games, web pages, or other purposes by procedural means.

While it may be attractive to view sensors as simple transducers which convert physical quantities into electrical signals, the truth of the matter is more complex.

Human decision-making often transcends our formal models of "e;rationality.

Partial differential equations (PDEs) are one of the most used widely forms of mathematics in science and engineering.

Partial differential equations (PDEs) are one of the most used widely forms of mathematics in science and engineering.

This book is a formalization of collected notes from an introductory game theory course taught at Queen's University.

Graphs naturally represent information ranging from links between web pages, to communication in email networks, to connections between neurons in our brains.

The Rust programming language is consistent and does its best to avoid surprising the programmer.

The Rust programming language is consistent and does its best to avoid surprising the programmer.

Self-driving cars, natural language recognition, and online recommendation engines are all possible thanks to Machine Learning.

Algorithms and data structures are much more than abstract concepts.

Algorithms and data structures are much more than abstract concepts.

From finance to artificial intelligence, genetic algorithms are a powerful tool with a wide array of applications.

From finance to artificial intelligence, genetic algorithms are a powerful tool with a wide array of applications.

This book contains 25 short programs that will challenge your understanding of Go.

This book contains 25 short programs that will challenge your understanding of Go.

Unlock the secrets to creating random mazes!

Unlock the secrets to creating random mazes!

When you write software, you need to be at the top of your game.

When you write software, you need to be at the top of your game.

This text covers all of the data science, machine learning, and deep learning topics relevant to materials science and engineering, accompanied by numerous examples and applications.

';We finally have the definitive treatise on PyTorch!

Learning and using groundbreaking generative AI tools like ChatGPT and Google Bard can take some time.

Theory is what remains true when technology is changing.

Blurring is almost an omnipresent effect on natural images.

Learning and using groundbreaking generative AI tools like ChatGPT and Google Bard can take some time.

This book results from many years of teaching an upper division course on communication networks in the EECS department at the University of California, Berkeley.

The last decade has seen an unprecedented growth in the demand for wireless services.

Most emerging applications in imaging and machine learning must perform immense amounts of computation while holding to strict limits on energy and power.

The congestion control mechanism has been responsible for maintaining stability as the Internet scaled up by many orders of magnitude in size, speed, traffic volume, coverage, and complexity over the last three decades.

Mathematics of Networks: Modulus Theory and Convex Optimization explores the question: "e;What can be learned by adapting the theory of p-modulus (and related continuum analysis concepts) to discrete graphs?

Genetic algorithms (GA) have become popular tools for search, optimization, machine learning, and solving design problems.

A complete guide on using data structures and algorithms to write sophisticated C# codeKey FeaturesMaster array, set and map with trees and graphs, among other fundamental data structuresDelve into effective design and implementation techniques to meet your software requirementsExplore illustrations to present data structures and algorithms, as well as their analysis in a clear, visual mannerBook DescriptionData structures allow organizing data efficiently.

This book is an instructional text that will teach you how to code x86-64 assembly language functions.

This book provides an insight into 12th International Conference on Soft Computing for Problem Solving (SocProS 2023), organized by The Department of Applied Mathematics and Scientific Computing, Saharanpur Campus of Indian Institute of Technology, Roorkee, India, in conjunction with Continuing Education Center during 11-13 August 2023.

Mathematics of Networks: Modulus Theory and Convex Optimization explores the question: "e;What can be learned by adapting the theory of p-modulus (and related continuum analysis concepts) to discrete graphs?

This combinatorics text provides in-depth coverage of recurrences, generating functions, partitions, and permutations, along with some of the most interesting graph and network topics, design constructions, and finite geometries.

Focusing on algorithms for distributed-memory parallel architectures, Parallel Algorithms presents a rigorous yet accessible treatment of theoretical models of parallel computation, parallel algorithm design for homogeneous and heterogeneous platforms, complexity and performance analysis, and essential notions of scheduling.

Algorithms and Theory of Computation Handbook, Second Edition: General Concepts and Techniques provides an up-to-date compendium of fundamental computer science topics and techniques.

Algorithms and Theory of Computation Handbook, Second Edition: Special Topics and Techniques provides an up-to-date compendium of fundamental computer science topics and techniques.

Beginning with the origin of the four color problem in 1852, the field of graph colorings has developed into one of the most popular areas of graph theory.