Artificial Intelligence Enabled Signal Processing Based Models For Neural Information Processing
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Artificial Intelligence Enabled Signal Processing Based Models for Neural Information Processing
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.
Artificial Intelligence Enabled Signal Processing based Models for Neural Information Processing
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.
Humanizing Technology With Emotional Intelligence
In an era where technology permeates every aspect of our lives, the imperative for sentient systems has never been greater. This necessity stems from the recognition that effective human-computer interaction (HCI) transcends mere transactional exchanges, aspiring instead to foster connections that are as nuanced and empathetic as those between humans. Emotional intelligence in computing systems, therefore, is not a luxury but a prerequisite for creating technologies that enhance, rather than hinder, our daily lives. Affective computing, the interdisciplinary domain at the heart of this endeavor, bridges the gap between human emotional experience and computational technology, aiming to imbue machines with the ability to detect, interpret, and respond to human emotions. Humanizing Technology With Emotional Intelligence delves into the why and how of incorporating emotional intelligence into computing systems. The book provides a comprehensive overview of both the theoretical foundations and the practical applications of affective computing in HCI. Covering topics such as automotive safety, holistic student development, and social robotics, this book is an excellent resource for academicians, researchers, graduate and postgraduate students, software developers, product managers, and more.