Chaurasiya Rahul (29 results)

Condition: New.

Condition: As New. Unread book in perfect condition.

Condition: As New. Unread book in perfect condition.

Condition: New.

Condition: New. 1st edition NO-PA16APR2015-KAP.

Condition: New.

Condition: New.

Hardback. Condition: New. New copy - Usually dispatched within 4 working days.

HRD. Condition: New. New Book. Shipped from UK. Established seller since 2000.

HRD. Condition: New. New Book. Shipped from UK. Established seller since 2000.

Hardback. Condition: 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. …

Hardcover. Condition: Brand New. 424 pages. 9.18x6.12x9.21 inches. In Stock.

Buch. Condition: 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. Condition: 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. Condition: 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. …

Condition: New.

Condition: As New. Unread book in perfect condition.

Condition: New.

Condition: New.

Condition: As New. Unread book in perfect condition.

Hardback. Condition: New.

Hardback. Condition: New.

Hardcover. Condition: new. Hardcover. 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, Alzheimers 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. 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. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…

Condition: New. PRINT ON DEMAND.

Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Dr. Rahul Kumar Chaurasiya is working as Associate Professor at Maulana Azad National Institute of Technology (MANIT) Bhopal, India. He received the Bachelor of Technology degree from MANIT Bhopal, India in 2009 and the Master of Engineering degre.…

HRD. Condition: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

HRD. Condition: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. KlappentextrnrnTechnological advancements have enhanced all functions of society and revolutionized the healthcare field. Smart healthcare applications and practices have grown within the past decade, strengthening overall care. Biomedical signa.…

Buch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Technological advancements have enhanced all functions of society and revolutionized the healthcare field. Smart healthcare applications and practices have grown within the past decade, strengthening overall care. Biomedical signals observe physiological activities, which provide essential information to healthcare professionals. Biomedical signal processing can be optimized through artificial intelligence (AI) and machine learning (ML), presenting the next step towards smart healthcare. AI-Enabled Smart Healthcare Using Biomedical Signals will not only cover the mathematical description of the AI- and ML-based methods, but also analyze and demonstrate the usability of different AI methods for a range of biomedical signals. The book covers all types of biomedical signals helpful for smart healthcare applications. Covering topics such as automated diagnosis, emotion identification, and frequency discrimination techniques, this premier reference source is an excellent resource for healthcare administration, biomedical engineers, medical laboratory technicians, medical technology assistants, computer scientists, libraries, students and faculty of higher education, researchers, and academicians. …