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Help
If you have any questions, you are always welcome to contact us. We'll get back to you as soon as possible, withing 24 hours on weekdays.
Customer service
All questions about your order, return and delivery must be sent to our customer service team by e-mail at yourstore@yourdomain.com
Sale & Press
If you are interested in selling our products, need more information about our brand or wish to make a collaboration, please contact us at press@yourdomain.com
Cet ouvrage prsente une introduction l'apprentissage statistique pour le signal dans le cadre des Interfaces CerveauMachine (ICM). Nous introduisons tout d'abord les ICM, qui sont des systmes visant contrler une machine par l'intermdiaire du cerveau. Nous proposons galement une introduction l'apprentissage statistique o l'on abordera la rgularisation et les a priori que cette dernire permet d'intgrer dans le processus d'apprentissage. Un rappel concernant les algorithmes d'optimisation utiliss en apprentissage statistique est galement fait. Nous prsentons ensuite deux mthodes d'apprentissage statistique pour le signal. Tous d'abord une mthode d'apprentissage de filtre permettant de maximiser la marge entre les exemples d'apprentissage, puis une approche multitche qui permet de transfrer de l'information entre plusieurs problmes d'apprentissage. Des applications de ces mthodes sont faites sur des donnes relles de type ICM.
⚠️ WARNING (California Proposition 65):
This product may contain chemicals known to the State of California to cause cancer,
birth defects, or other reproductive harm.
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