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
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Artificial Intelligence Enabled Signal Processing based Models for Neural Information Processing
Description
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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