
Автор: Yang Chai, Fuyou Liao
Издательство: Springer
Год: 2022
Страниц: 237
Язык: английский
Формат: pdf (true)
Размер: 17.1 MB
This book provides a detailed introduction to near-sensor and in-sensor computing paradigms, their working mechanisms, development trends and future directions. The authors also provide a comprehensive review of current progress in this area, analyze existing challenges in the field, and offer possible solutions. Readers will benefit from the discussion of computing approaches that intervene in the vicinity of or inside sensory networks to help process data more efficiently, decreasing power consumption and reducing the transfer of redundant data between sensing and processing units. Neuromorphic computing dreams of human-level artificial general intelligence by emulating the brain, which contrasts the pervasive von Neumann computing architecture. Up to now, artificial synapses have been long and widely adapted to function mostly as signal transmission with a memory effect in neuromorphic computing; significant efforts have been made to mimic mostly the memory function (e.g., memristors). However, emulating synaptic computation, which is vital for information processing, working memory, and decision-making by using short-term plasticity (STP), remains technically challenging to be demonstrated without using numerous CMOS devices. In the human brain, a quadrillion synapses are present in a massively parallel architecture, which highlights the issue of integration of CMOS devices for an efficient neuromorphic chip.