دانلود کتاب A Neuromorphic Multiplier-Less Bit-Serial Weight- Memory-Optimized 1024-Tree Brain-State Classifier and Neuromodulation SoC with an 8-Channel Noise-Shaping SAR ADC Array

Name: A Neuromorphic Multiplier-Less Bit-Serial Weight- Memory-Optimized 1024-Tree Brain-State Classifier and Neuromodulation SoC with an 8-Channel Noise-Shaping SAR ADC Array
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Author: Gerard O'Leary
ISBN: 9781728132051

by Gerard O'Leary, Jianxiong Xu, Liam Long, Jose Sales Filho, Camilo Tejeiro, Maged ElAnsary, Chenxi Tang, Homeira Moradi, Prajay Shah, Taufik A. Valiante, Roman Genovl University of Toronto

عنوان فارسی: یک Neuromorphic چند برابر کمتر بیت-سریال وزن - حافظه-بهینه سازی 1024-درخت مغز-دولت طبقه بندی و Neuromodulation SoC با 8 کانال صدا-شکل گیری SAR ADC آرایه
ناشر: IEEE
سال: 2020
زبان: انگلیسی
تعداد صفحه (نسخه چاپی - نسخه الکترونیکی): 3
شابک: 9781728132051
نوع فایل: PDF دانلود نرم افزار مطالعه
حجم: 1.61 مگابایت

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Personalized medical brain implants have the potential to revolutionize the treatment of neurological disorders and augment cognition. Critically, these devices require accurate, energy-efficient brain-state classifiers to determine the precise moment when the treatment neuromodulation efficacy is maximized, such as before the onset of a seizure in epilepsy [1]. The SoC presented in this work addresses this requirement by combining a bank of 8 neural signal ADCs with BrainForest, an accurate, low-power classification core comprised of a 1024-tree exponentially decaying memory decision forest (EDM-DF). Full closed-loop neuromodulation is supported through the responsive actuation of an on-chip electrical neurostimulator.