Brain-Machine Interface Engineering
Sanchez, Justin Cort
Brain-Machine Interface Engineering by Justin Sanchez, José C. Príncipe - 1st edition 2007 - 1 recurso en línea (X, 234 páginas) - Synthesis Lectures on Biomedical Engineering 1930-0336 .
Contents: Introduction to Neural Interfaces -- Foundations of Neuronal Representations -- Input-Outpur BMI Models -- Regularization Techniques for BMI Models -- Neural Decoding Using Generative BMI Models -- Adaptive Algorithms for Point Processes -- BMI Systems.
Neural interfaces are one of the most exciting emerging technologies to impact bioengineering and neuroscience because they enable an alternate communication channel linking directly the nervous system with man-made devices. This book reveals the essential engineering principles and signal processing tools for deriving control commands from bioelectric signals in large ensembles of neurons. The topics featured include analysis techniques for determining neural representation, modeling in motor systems, computing with neural spikes, and hardware implementation of neural interfaces. Beginning with an exploration of the historical developments that have led to the decoding of information from neural interfaces, this book compares the theory and performance of new neural engineering approaches for BMIs. Contents: Introduction to Neural Interfaces / Foundations of Neuronal Representations / Input-Outpur BMI Models / Regularization Techniques for BMI Models / Neural Decoding Using Generative BMI Models / Adaptive Algorithms for Point Processes / BMI Systems.
9783031016219
10.1007/978-3-031-01621-9 doi
Interfaces cerebro-ordenador
Bioingeniería
Redes neuronales artificiales
QP360.7 / 2007 EB
Brain-Machine Interface Engineering by Justin Sanchez, José C. Príncipe - 1st edition 2007 - 1 recurso en línea (X, 234 páginas) - Synthesis Lectures on Biomedical Engineering 1930-0336 .
Contents: Introduction to Neural Interfaces -- Foundations of Neuronal Representations -- Input-Outpur BMI Models -- Regularization Techniques for BMI Models -- Neural Decoding Using Generative BMI Models -- Adaptive Algorithms for Point Processes -- BMI Systems.
Neural interfaces are one of the most exciting emerging technologies to impact bioengineering and neuroscience because they enable an alternate communication channel linking directly the nervous system with man-made devices. This book reveals the essential engineering principles and signal processing tools for deriving control commands from bioelectric signals in large ensembles of neurons. The topics featured include analysis techniques for determining neural representation, modeling in motor systems, computing with neural spikes, and hardware implementation of neural interfaces. Beginning with an exploration of the historical developments that have led to the decoding of information from neural interfaces, this book compares the theory and performance of new neural engineering approaches for BMIs. Contents: Introduction to Neural Interfaces / Foundations of Neuronal Representations / Input-Outpur BMI Models / Regularization Techniques for BMI Models / Neural Decoding Using Generative BMI Models / Adaptive Algorithms for Point Processes / BMI Systems.
9783031016219
10.1007/978-3-031-01621-9 doi
Interfaces cerebro-ordenador
Bioingeniería
Redes neuronales artificiales
QP360.7 / 2007 EB