Artificial intelligence based signal processing (27 Ergebnisse)

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Zustand: New. Rajesh Kumar Tripathy received a B.Tech degree in Electronics and Telecommunication Engineering from the Biju Patnaik University of Technology (BPUT), Odisha, India, in 2009 and the M.Tech degree in Biomedical Engineering from the National Instit.

Taschenbuch. Zustand: Neu. Neuware - 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.…

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Hardback. Zustand: New. 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 signalsPresents automated methods for detection of neurological disorders and other applications such as cognitive task recognition, and brain-computer interfaceHighlights the latest machine learning and deep learning methods for neural signal processingDiscusses mathematical details for the signal processing and machine learning algorithms applied for electroencephalography data analysisShowcases the detection of dementia from electroencephalography signals using signal processing and machine learning-based techniquesIt is primarily written for senior undergraduates, graduate students, and researchers in the fields of electrical engineering, electronics and communications engineering, and biomedical engineering.…

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Hardback. Zustand: New. Artificial Intelligence-based Signal Processing for Brain Activity Analysis is an indispensable resource for addressing the pressing challenges in medicine, detection of brain-related disorders, brain-computer interfacing, and neuromarketing. It delves into contemporary AI, ML, and signal processing approaches for analysis of brain activity.The salient features of this book include:(1) Acquisition, preprocessing, noise removal, and processing methods for brain signals, including EEG, ECoG, MEG, fMRI, and fNIRS.(2) Latest AI and ML algorithms relevant for classification of brain signals, including traditional machine learners, deep transfer learners, LSTM and auto-encoders, and transformers.(3) Applications in medicine, including mental healthcare, mental stress reduction, psychological disorder detection, OCD detection, sleep disorder detection, seizure detection, brain tumor detection, Alzheimer's disease detection, and bipolar disorder prediction.(4) Applications in brain-computer interfacing (BCI), gaming and entertainment, and neuromarketing.(5) Recent case studies and experimental and research works.The text is primarily written for senior undergraduate students, graduate students, industry professionals, researchers, and academicians working in the field of AI, ML, signal processing techniques, biomedical signal processing, brain signal analysis, and brain activity analysis. …

Hardback. Zustand: New. 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 signalsPresents automated methods for detection of neurological disorders and other applications such as cognitive task recognition, and brain-computer interfaceHighlights the latest machine learning and deep learning methods for neural signal processingDiscusses mathematical details for the signal processing and machine learning algorithms applied for electroencephalography data analysisShowcases the detection of dementia from electroencephalography signals using signal processing and machine learning-based techniquesIt is primarily written for senior undergraduates, graduate students, and researchers in the fields of electrical engineering, electronics and communications engineering, and biomedical engineering.…

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Buch. Zustand: Neu. Artificial Intelligence-based Signal Processing for Brain Activity Analysis | Rahul Chaurasiya (u. a.) | Buch | Einband - fest (Hardcover) | Englisch | 2025 | CRC Press | EAN 9781032896724 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu. …

Buch. Zustand: Neu. Neuware - Artificial Intelligence-based Signal Processing for Brain Activity Analysis is an indispensable resource for addressing the pressing challenges in medicine, detection of brain related disorders, brain-computer interfacing, and neuromarketing. It delves into contemporary AI, ML, and signal processing approaches for analysis of brain activity.…

Hardback. Zustand: New. Artificial Intelligence-based Signal Processing for Brain Activity Analysis is an indispensable resource for addressing the pressing challenges in medicine, detection of brain-related disorders, brain-computer interfacing, and neuromarketing. It delves into contemporary AI, ML, and signal processing approaches for analysis of brain activity.The salient features of this book include:(1) Acquisition, preprocessing, noise removal, and processing methods for brain signals, including EEG, ECoG, MEG, fMRI, and fNIRS.(2) Latest AI and ML algorithms relevant for classification of brain signals, including traditional machine learners, deep transfer learners, LSTM and auto-encoders, and transformers.(3) Applications in medicine, including mental healthcare, mental stress reduction, psychological disorder detection, OCD detection, sleep disorder detection, seizure detection, brain tumor detection, Alzheimer's disease detection, and bipolar disorder prediction.(4) Applications in brain-computer interfacing (BCI), gaming and entertainment, and neuromarketing.(5) Recent case studies and experimental and research works.The text is primarily written for senior undergraduate students, graduate students, industry professionals, researchers, and academicians working in the field of AI, ML, signal processing techniques, biomedical signal processing, brain signal analysis, and brain activity analysis. …