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Article

Natural Brain-Inspired Intelligence for Non-Gaussian and Nonlinear Environments with Finite Memory

Dept of Electrical and Computer Engineering, McMaster University, Hamilton, ON L8S 4L8, Canada
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Appl. Sci. 2020, 10(3), 1150; https://doi.org/10.3390/app10031150
Received: 30 November 2019 / Revised: 4 February 2020 / Accepted: 4 February 2020 / Published: 8 February 2020
The cyber processing layer of smart systems based on a cognitive dynamic system (CDS) can be a good solution for better decision making and situation understanding in non-Gaussian and nonlinear environments (NGNLE). The NGNLE situation understanding means deciding between certain known situations in NGNLE to understand the current state condition. Here, we report on a cognitive decision-making (CDM) system inspired by the human brain decision-making. The simple low-complexity algorithmic design of the proposed CDM system can make it suitable for real-time applications. A case study of the implementation of the CDS on a long-haul fiber-optic orthogonal frequency division multiplexing (OFDM) link was performed. An improvement in Q-factor of ~7 dB and an enhancement in data rate efficiency ~43% were achieved using the proposed algorithms. Furthermore, an extra 20% data rate enhancement was obtained by guaranteeing to keep the CDM error automatically under the system threshold. The proposed system can be extended as a general software-based platform for brain-inspired decision making in smart systems in the presence of nonlinearity and non-Gaussian characteristics. Therefore, it can easily upgrade the conventional systems to a smart one for autonomic CDM applications. View Full-Text
Keywords: autonomic decision-making system; autonomic computing layer; cognitive dynamic system; cognitive decision making; non-Gaussian and non-linear environment; focus level concept; situation understanding; smart systems autonomic decision-making system; autonomic computing layer; cognitive dynamic system; cognitive decision making; non-Gaussian and non-linear environment; focus level concept; situation understanding; smart systems
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MDPI and ACS Style

Naghshvarianjahromi, M.; Kumar, S.; Deen, M.J. Natural Brain-Inspired Intelligence for Non-Gaussian and Nonlinear Environments with Finite Memory. Appl. Sci. 2020, 10, 1150. https://doi.org/10.3390/app10031150

AMA Style

Naghshvarianjahromi M, Kumar S, Deen MJ. Natural Brain-Inspired Intelligence for Non-Gaussian and Nonlinear Environments with Finite Memory. Applied Sciences. 2020; 10(3):1150. https://doi.org/10.3390/app10031150

Chicago/Turabian Style

Naghshvarianjahromi, Mahdi, Shiva Kumar, and M. J. Deen 2020. "Natural Brain-Inspired Intelligence for Non-Gaussian and Nonlinear Environments with Finite Memory" Applied Sciences 10, no. 3: 1150. https://doi.org/10.3390/app10031150

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