One-step Calculation Circuit of Blind Signal Detection using Complex-valued Hopfield Neural Network

HONG Qinghui; SUN Chen; XIAO Pingdan; WEI Zhengmiao; DU Sichun

doi:10.11999/JEIT240224

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HONG Qinghui, SUN Chen, XIAO Pingdan, WEI Zhengmiao, DU Sichun. One-step Calculation Circuit of Blind Signal Detection using Complex-valued Hopfield Neural Network[J]. Journal of Electronics & Information Technology. doi: 10.11999/JEIT240224

Citation:

HONG Qinghui, SUN Chen, XIAO Pingdan, WEI Zhengmiao, DU Sichun. One-step Calculation Circuit of Blind Signal Detection using Complex-valued Hopfield Neural Network[J]. Journal of Electronics & Information Technology. doi: 10.11999/JEIT240224

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One-step Calculation Circuit of Blind Signal Detection using Complex-valued Hopfield Neural Network

doi: 10.11999/JEIT240224

College of Information Science and Engineering, Hunan University, Changsha 410082, China

Funds: The National Natural Science Foundation of China (62234008,62371186), Huxiang Young Talents Project (2023RC3103), Natural Science Foundation of Hunan Province(2023JJ30168, 2022JJ30160, 2021JJ40111), National Key R&D Program of China (2022YFB3903800)

Received Date: 2024-03-29
Rev Recd Date: 2024-10-11

Available Online: 2024-10-16

Abstract

Abstract

Blind signal detection is of great significance in large-scale communication networks and has been widely used. How to quickly obtain blind signal detection results is an urgent need for the new generation of real-time communication networks. Considering this demand, a Complex-valued Hopfield neural Network (CHNN) circuit is designed that can accelerate blind signal detection from an analog circuit perspective, the proposed circuit can accelerate the blind signal detection by rapidly performing massively parallel calculation in one step. At the same time, the circuit can be programmable by adjusting the conductance and input voltage of the memristor. The Pspice simulation results show that the computing accuracy of the proposed circuit can exceed 99%. Compared with Matlab software simulation, the proposed circuit is three orders of magnitude faster in terms of computing time. And the accuracy can be maintained at more than 99% even under the interference of 20% noise.
- Circuit design,
- Memristor,
- Complex-valued Hopfield Neural Network(CHNN),
- Blind signal detection

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References(22)

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