TY - JOUR
T1 - Artificial Sensory Memory
AU - Wan, Changjin
AU - Cai, Pingqiang
AU - Wang, Ming
AU - Qian, Yan
AU - Huang, Wei
AU - Chen, Xiaodong
N1 - Publisher Copyright:
© 2019 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim
PY - 2020/4/1
Y1 - 2020/4/1
N2 - Sensory memory, formed at the beginning while perceiving and interacting with the environment, is considered a primary source of intelligence. Transferring such biological concepts into electronic implementation aims at achieving perceptual intelligence, which would profoundly advance a broad spectrum of applications, such as prosthetics, robotics, and cyborg systems. Here, the recent developments in the design and fabrication of artificial sensory memory devices are summarized and their applications in recognition, manipulation, and learning are highlighted. The emergence of such devices benefits from recent progress in both bioinspired sensing and neuromorphic engineering technologies and derives from abundant inspiration and benchmarks from an improved understanding of biological sensory processing. Increasing attention to this area would offer unprecedented opportunities toward new hardware architecture of artificial intelligence, which could extend the capabilities of digital systems with emotional/psychological attributes. Pending challenges are also addressed to aspects such as integration level, energy efficiency, and functionality, which would undoubtedly shed light on the future development of translational implementations.
AB - Sensory memory, formed at the beginning while perceiving and interacting with the environment, is considered a primary source of intelligence. Transferring such biological concepts into electronic implementation aims at achieving perceptual intelligence, which would profoundly advance a broad spectrum of applications, such as prosthetics, robotics, and cyborg systems. Here, the recent developments in the design and fabrication of artificial sensory memory devices are summarized and their applications in recognition, manipulation, and learning are highlighted. The emergence of such devices benefits from recent progress in both bioinspired sensing and neuromorphic engineering technologies and derives from abundant inspiration and benchmarks from an improved understanding of biological sensory processing. Increasing attention to this area would offer unprecedented opportunities toward new hardware architecture of artificial intelligence, which could extend the capabilities of digital systems with emotional/psychological attributes. Pending challenges are also addressed to aspects such as integration level, energy efficiency, and functionality, which would undoubtedly shed light on the future development of translational implementations.
KW - artificial neurons
KW - bioinspired sensors
KW - memory
KW - neuromorphic engineering
UR - http://www.scopus.com/inward/record.url?scp=85070265618&partnerID=8YFLogxK
U2 - 10.1002/adma.201902434
DO - 10.1002/adma.201902434
M3 - 文献综述
C2 - 31364219
AN - SCOPUS:85070265618
SN - 0935-9648
VL - 32
JO - Advanced Materials
JF - Advanced Materials
IS - 15
M1 - 1902434
ER -