TY - CHAP
T1 - Memristive threshold logic networks
AU - Dolzhikova, Irina
AU - Kumar Maan, Akshay
AU - James Pappachen, Alex
PY - 2020/1/1
Y1 - 2020/1/1
N2 - Threshold logic gates (TLGs) are known for high-speed and low power consumption, which is essential for applications such as real-time processing and recognition of natural signals, as well as on-chip memory architecture and neural network implementation. Integration of memristors into the design allows extending the capabilities of threshold logic circuits. In this chapter, we review the hardware designs of memristive threshold logic (MTL) circuits that are inspired by the principle of neuron firing inside the brain. Variety of threshold architectures, their limitations and possible field of application are discussed.
AB - Threshold logic gates (TLGs) are known for high-speed and low power consumption, which is essential for applications such as real-time processing and recognition of natural signals, as well as on-chip memory architecture and neural network implementation. Integration of memristors into the design allows extending the capabilities of threshold logic circuits. In this chapter, we review the hardware designs of memristive threshold logic (MTL) circuits that are inspired by the principle of neuron firing inside the brain. Variety of threshold architectures, their limitations and possible field of application are discussed.
UR - http://www.scopus.com/inward/record.url?scp=85064733990&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85064733990&partnerID=8YFLogxK
U2 - 10.1007/978-3-030-14524-8_9
DO - 10.1007/978-3-030-14524-8_9
M3 - Chapter
AN - SCOPUS:85064733990
T3 - Modeling and Optimization in Science and Technologies
SP - 117
EP - 130
BT - Modeling and Optimization in Science and Technologies
PB - Springer Verlag
ER -