Artificial Intelligence Enabled Signal Processing Based Models For Neural Information Processing
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Author | : Rajesh Kumar Tripathy |
Publisher | : CRC Press |
Total Pages | : 227 |
Release | : 2024-06-06 |
Genre | : Technology & Engineering |
ISBN | : 1040028772 |
The book provides details regarding the application of various signal processing and artificial intelligence-based methods for electroencephalography data analysis. It will help readers in understanding the use of electroencephalography signals for different neural information processing and cognitive neuroscience applications. The book: Covers topics related to the application of signal processing and machine learning-based techniques for the analysis and classification of electroencephalography signals Presents automated methods for detection of neurological disorders and other applications such as cognitive task recognition, and brain-computer interface Highlights the latest machine learning and deep learning methods for neural signal processing Discusses mathematical details for the signal processing and machine learning algorithms applied for electroencephalography data analysis Showcases the detection of dementia from electroencephalography signals using signal processing and machine learning-based techniques It is primarily written for senior undergraduates, graduate students, and researchers in the fields of electrical engineering, electronics and communications engineering, and biomedical engineering.
Author | : Robert Kozma |
Publisher | : Academic Press |
Total Pages | : 398 |
Release | : 2023-10-11 |
Genre | : Computers |
ISBN | : 0323958168 |
Artificial Intelligence in the Age of Neural Networks and Brain Computing, Second Edition demonstrates that present disruptive implications and applications of AI is a development of the unique attributes of neural networks, mainly machine learning, distributed architectures, massive parallel processing, black-box inference, intrinsic nonlinearity, and smart autonomous search engines. The book covers the major basic ideas of "brain-like computing" behind AI, provides a framework to deep learning, and launches novel and intriguing paradigms as possible future alternatives. The present success of AI-based commercial products proposed by top industry leaders, such as Google, IBM, Microsoft, Intel, and Amazon, can be interpreted using the perspective presented in this book by viewing the co-existence of a successful synergism among what is referred to as computational intelligence, natural intelligence, brain computing, and neural engineering. The new edition has been updated to include major new advances in the field, including many new chapters. - Developed from the 30th anniversary of the International Neural Network Society (INNS) and the 2017 International Joint Conference on Neural Networks (IJCNN - Authored by top experts, global field pioneers, and researchers working on cutting-edge applications in signal processing, speech recognition, games, adaptive control and decision-making - Edited by high-level academics and researchers in intelligent systems and neural networks - Includes all new chapters, including topics such as Frontiers in Recurrent Neural Network Research; Big Science, Team Science, Open Science for Neuroscience; A Model-Based Approach for Bridging Scales of Cortical Activity; A Cognitive Architecture for Object Recognition in Video; How Brain Architecture Leads to Abstract Thought; Deep Learning-Based Speech Separation and Advances in AI, Neural Networks
Author | : Iyad Obeid |
Publisher | : Springer Nature |
Total Pages | : 261 |
Release | : 2021-04-12 |
Genre | : Technology & Engineering |
ISBN | : 3030674940 |
This book provides an interdisciplinary look at emerging trends in signal processing and biomedicine found at the intersection of healthcare, engineering, and computer science. It examines the vital role signal processing plays in enabling a new generation of technology based on big data, and looks at applications ranging from medical electronics to data mining of electronic medical records. Topics covered include analysis of medical images, machine learning, biomedical nanosensors, wireless technologies, and instrumentation and electrical stimulation. Biomedical Signal Processing: Innovation and Applications presents tutorials and examples of successful applications, and will appeal to a wide range of professionals, researchers, and students interested in applications of signal processing, medicine, and biology.
Author | : Nilanjan Dey |
Publisher | : Academic Press |
Total Pages | : 210 |
Release | : 2019-04-02 |
Genre | : Technology & Engineering |
ISBN | : 0128181303 |
Intelligent Speech Signal Processing investigates the utilization of speech analytics across several systems and real-world activities, including sharing data analytics, creating collaboration networks between several participants, and implementing video-conferencing in different application areas. Chapters focus on the latest applications of speech data analysis and management tools across different recording systems. The book emphasizes the multidisciplinary nature of the field, presenting different applications and challenges with extensive studies on the design, development and management of intelligent systems, neural networks and related machine learning techniques for speech signal processing.
Author | : Li Deng |
Publisher | : |
Total Pages | : 212 |
Release | : 2014 |
Genre | : Machine learning |
ISBN | : 9781601988140 |
Provides an overview of general deep learning methodology and its applications to a variety of signal and information processing tasks
Author | : Catherine Prentice |
Publisher | : Springer Nature |
Total Pages | : 180 |
Release | : 2023-05-11 |
Genre | : Computers |
ISBN | : 9819918650 |
This book takes a fresh stance and views EI and AI as services that are provided by service employees and machines as organisational offerings to customers. As emotional intelligence (EI) and artificial intelligence (AI) have been cited to have broad effects on individuals, businesses and beyond, this book is focused on the organisational context, specifically how they affect employees and customers from a marketing perspective. The stance in this book is consistent with the conceptualisation of a service. This book holds that intelligence in businesses must turn into organisational assets to manifest their values. Further, this book explores this service-dominant logic era, and compared to tangible products, service plays a key role in organisational performance and customer relationship with the organisation. Intelligence exhibited either by human or machine is not a tangible product, but can be utilised as a service to assist employees in performing tasks and delivering services as well as facilitating business transaction and customer experience. This book is structured as follows. Chapters 2 and 3 demystify emotional and artificial intelligence, from different perspectives, including conceptualisations, the history and evolution of the concepts, how they function and where they can apply to. These discussions help readers understand what exactly these two intelligences are. Chapters 4 and 5 analyse how emotional intelligence is related to employees and customers, respectively, with a focus on service organisations. Chapters 6–8 are dedicated to anatomising AI and how it is operationalised as a service to influence employees and customers. Specifically, viewing AI as a service, Chapter 6 examines the impact of AI service quality and how it is related to employee service quality. Chapter 7 analyses the influence of AI service quality on customers. Based on the discussion in Chapters 6 and 7, Chapter 8 is extended to develop a scale to measure such AI service, named AI service quality. The last three chapters of this book integrate EI and AI to analyse their respective impacts on employees and customers. Chapter 9 proposes EI as a moderator of AI, whereas Chapter 10 proposes AI as a moderator of EI. Chapter 11 employs service profit chain to integrate EI and AI in the chain relationship to understand their effects on both employees and customers. This chapter broadly covers the service industry with a focus on tourism and hospitality sector. The discussion on the impact of EI and AI is complemented with empirical studies conducted in tourism or hospitality context to address their effects in these sectors.
Author | : |
Publisher | : Elsevier |
Total Pages | : 3607 |
Release | : 2002-07-04 |
Genre | : Science |
ISBN | : 0080548032 |
In the past decade, enormous strides have been made in understanding the human brain. The advent of sophisticated new imaging techniques (e.g. PET, MRI, MEG, etc.) and new behavioral testing procedures have revolutionized our understanding of the brain, and we now know more about the anatomy, functions, and development of this organ than ever before. However, much of this knowledge is scattered across scientific journals and books in a diverse group of specialties: psychology, neuroscience, medicine, etc. The Encyclopedia of the Human Brain places all information in a single source and contains clearly written summaries on what is known of the human brain. Covering anatomy, physiology, neuropsychology, clinical neurology, neuropharmacology, evolutionary biology, genetics, and behavioral science, this four-volume encyclopedia contains over 200 peer reviewed signed articles from experts around the world. The Encyclopedia articles range in size from 5-30 printed pages each, and contain a definition paragraph, glossary, outline, and suggested readings, in addition to the body of the article. Lavishly illustrated, the Encyclopedia includes over 1000 figures, many in full color. Managing both breadth and depth, the Encyclopedia is a must-have reference work for life science libraries and researchers investigating the human brain.
Author | : Rubee Singh |
Publisher | : Walter de Gruyter GmbH & Co KG |
Total Pages | : 288 |
Release | : 2024-06-04 |
Genre | : Business & Economics |
ISBN | : 3111172406 |
Companies in developing countries are adopting Artificial Intelligence applications to increase efficiency and open new markets for their products. This book explores the multifarious capabilities and applications of AI in the context of these emerging economies and its role as a driver for decision making in current management practices. Artificial Intelligence Enabled Management argues that the economic problems facing academics, professionals, managers, governments, businesses and those at the bottom of the economic pyramid have a technical solution that relates to AI. Businesses in developing countries are using cutting-edge AI-based solutions to improve autonomous delivery of goods and services, implement automation of production and develop mobile apps for services and access to credit. By integrating data from websites, social media and conventional channels, companies are developing data management platforms, good business plans and creative business models. By increasing productivity, automating business processes, financial solutions and government services, AI can drive economic growth in these emerging economies. Public and private sectors can work together to find innovative solutions that simultaneously alleviate poverty and inequality and increase economic mobility and prosperity. The thought-provoking contributions in this book also bring attention to new barriers that have emerged in the acceptance, use, integration and deployment of AI by businesses in developing countries and explore the often-overlooked drawbacks of AI adoption that can hinder or even cause value loss. The book is a must-read for policymakers, researchers, and anyone interested in understanding the critical role of AI in the emerging economy perspective.
Author | : Yu Hen Hu |
Publisher | : CRC Press |
Total Pages | : 408 |
Release | : 2018-10-03 |
Genre | : Technology & Engineering |
ISBN | : 1420038613 |
The use of neural networks is permeating every area of signal processing. They can provide powerful means for solving many problems, especially in nonlinear, real-time, adaptive, and blind signal processing. The Handbook of Neural Network Signal Processing brings together applications that were previously scattered among various publications to provide an up-to-date, detailed treatment of the subject from an engineering point of view. The authors cover basic principles, modeling, algorithms, architectures, implementation procedures, and well-designed simulation examples of audio, video, speech, communication, geophysical, sonar, radar, medical, and many other signals. The subject of neural networks and their application to signal processing is constantly improving. You need a handy reference that will inform you of current applications in this new area. The Handbook of Neural Network Signal Processing provides this much needed service for all engineers and scientists in the field.
Author | : Adam Bohr |
Publisher | : Academic Press |
Total Pages | : 385 |
Release | : 2020-06-21 |
Genre | : Computers |
ISBN | : 0128184396 |
Artificial Intelligence (AI) in Healthcare is more than a comprehensive introduction to artificial intelligence as a tool in the generation and analysis of healthcare data. The book is split into two sections where the first section describes the current healthcare challenges and the rise of AI in this arena. The ten following chapters are written by specialists in each area, covering the whole healthcare ecosystem. First, the AI applications in drug design and drug development are presented followed by its applications in the field of cancer diagnostics, treatment and medical imaging. Subsequently, the application of AI in medical devices and surgery are covered as well as remote patient monitoring. Finally, the book dives into the topics of security, privacy, information sharing, health insurances and legal aspects of AI in healthcare. - Highlights different data techniques in healthcare data analysis, including machine learning and data mining - Illustrates different applications and challenges across the design, implementation and management of intelligent systems and healthcare data networks - Includes applications and case studies across all areas of AI in healthcare data