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Natural Intelligence as the Brain of Intelligent Systems.

Mahdi Naghshvarianjahromi1, Shiva Kumar1, Mohammed Jamal Deen1

  • 1Department of Electrical and Computer Engineering, McMaster University, Hamilton, ON L8S 4K1, Canada.

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Summary

Cognitive dynamic systems (CDS), inspired by the brain, offer promising advancements in intelligent systems. Their application in areas like cognitive radar and smart grids shows improved accuracy and performance with lower costs.

Keywords:
cognitive control (CC)cognitive decision makingcognitive dynamic system (CDS)cognitive radar (CR)cognitive radiocognitive risk control (CRC)cognitive vehicular communications (CVC)coordinated cognitive risk control (C-CRC)cyber securityfixed transmit waveform (FTW) radarfore-active radar (FAR)linear Gaussian environment (LGE)mutual interference (MI)nonlinear non-Gaussian environment (NGNLE)perception action cycle (PAC)perception multiple actions cycle (PMAC)self-driving carsmart e-healthsmart grid (SG)software-defined optical communication system (SDOCS)traditional active radar (TAR)vehicular radar systems (VRS)

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Area of Science:

  • Intelligent Systems and Cybernetics
  • Brain-Inspired Computing

Background:

  • Cognitive Dynamic Systems (CDS) are intelligent systems modeled after the brain's processing capabilities.
  • CDS are categorized into two branches: one for linear and Gaussian environments (LGEs) and another for non-Gaussian and nonlinear environments (NGNLEs).
  • Both branches utilize the perception-action cycle (PAC) for decision-making.

Purpose of the Study:

  • To review the diverse applications of Cognitive Dynamic Systems (CDS).
  • To highlight the effectiveness of CDS in both linear/Gaussian and non-Gaussian/nonlinear environments.
  • To showcase the benefits of CDS implementation in various technological domains.

Main Methods:

  • Review of CDS applications in linear and Gaussian environments (LGEs), including cognitive radio, cognitive radar, cognitive control, cyber security, self-driving cars, and smart grids.
  • Review of CDS applications in non-Gaussian and nonlinear environments (NGNLEs), focusing on smart e-healthcare and software-defined optical communication systems (SDOCS).
  • Analysis of the perception-action cycle (PAC) as the core decision-making principle in CDS.

Main Results:

  • CDS implementation in cognitive radars demonstrated superior performance, achieving range estimation error of 0.47m and velocity estimation error of 3.30m/s.
  • CDS application in smart fiber optic links resulted in a 7 dB quality factor improvement and a 43% increase in maximum achievable data rate.
  • Overall, CDS implementation shows promising results with enhanced accuracy, improved performance, and reduced computational costs across various applications.

Conclusions:

  • Cognitive Dynamic Systems (CDS) offer significant advantages in a wide array of intelligent applications.
  • The perception-action cycle (PAC) enables effective decision-making for CDS in diverse environmental conditions.
  • CDS represent a powerful approach for advancing technologies in fields ranging from radar to telecommunications and smart systems.