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Natural Intelligence as the Brain of Intelligent Systems
This article discusses the concept and applications of cognitive dynamic systems (CDS), which are a type of intelligent system inspired by the brain. There are two branches of CDS, one for linear and Gaussian environments (LGEs), such as cognitive radio and cognitive radar, and another one for non-G...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10007130/ https://www.ncbi.nlm.nih.gov/pubmed/36905061 http://dx.doi.org/10.3390/s23052859 |
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author | Naghshvarianjahromi, Mahdi Kumar, Shiva Deen, Mohammed Jamal |
author_facet | Naghshvarianjahromi, Mahdi Kumar, Shiva Deen, Mohammed Jamal |
author_sort | Naghshvarianjahromi, Mahdi |
collection | PubMed |
description | This article discusses the concept and applications of cognitive dynamic systems (CDS), which are a type of intelligent system inspired by the brain. There are two branches of CDS, one for linear and Gaussian environments (LGEs), such as cognitive radio and cognitive radar, and another one for non-Gaussian and nonlinear environments (NGNLEs), such as cyber processing in smart systems. Both branches use the same principle, called the perception action cycle (PAC), to make decisions. The focus of this review is on the applications of CDS, including cognitive radios, cognitive radar, cognitive control, cyber security, self-driving cars, and smart grids for LGEs. For NGNLEs, the article reviews the use of CDS in smart e-healthcare applications and software-defined optical communication systems (SDOCS), such as smart fiber optic links. The results of implementing CDS in these systems are very promising, with improved accuracy, performance, and lower computational costs. For example, CDS implementation in cognitive radars achieved a range estimation error that is as good as 0.47 (m) and a velocity estimation error of 3.30 (m/s), outperforming traditional active radars. Similarly, CDS implementation in smart fiber optic links improved the quality factor by 7 dB and the maximum achievable data rate by 43% compared to those of other mitigation techniques. |
format | Online Article Text |
id | pubmed-10007130 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-100071302023-03-12 Natural Intelligence as the Brain of Intelligent Systems Naghshvarianjahromi, Mahdi Kumar, Shiva Deen, Mohammed Jamal Sensors (Basel) Review This article discusses the concept and applications of cognitive dynamic systems (CDS), which are a type of intelligent system inspired by the brain. There are two branches of CDS, one for linear and Gaussian environments (LGEs), such as cognitive radio and cognitive radar, and another one for non-Gaussian and nonlinear environments (NGNLEs), such as cyber processing in smart systems. Both branches use the same principle, called the perception action cycle (PAC), to make decisions. The focus of this review is on the applications of CDS, including cognitive radios, cognitive radar, cognitive control, cyber security, self-driving cars, and smart grids for LGEs. For NGNLEs, the article reviews the use of CDS in smart e-healthcare applications and software-defined optical communication systems (SDOCS), such as smart fiber optic links. The results of implementing CDS in these systems are very promising, with improved accuracy, performance, and lower computational costs. For example, CDS implementation in cognitive radars achieved a range estimation error that is as good as 0.47 (m) and a velocity estimation error of 3.30 (m/s), outperforming traditional active radars. Similarly, CDS implementation in smart fiber optic links improved the quality factor by 7 dB and the maximum achievable data rate by 43% compared to those of other mitigation techniques. MDPI 2023-03-06 /pmc/articles/PMC10007130/ /pubmed/36905061 http://dx.doi.org/10.3390/s23052859 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Review Naghshvarianjahromi, Mahdi Kumar, Shiva Deen, Mohammed Jamal Natural Intelligence as the Brain of Intelligent Systems |
title | Natural Intelligence as the Brain of Intelligent Systems |
title_full | Natural Intelligence as the Brain of Intelligent Systems |
title_fullStr | Natural Intelligence as the Brain of Intelligent Systems |
title_full_unstemmed | Natural Intelligence as the Brain of Intelligent Systems |
title_short | Natural Intelligence as the Brain of Intelligent Systems |
title_sort | natural intelligence as the brain of intelligent systems |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10007130/ https://www.ncbi.nlm.nih.gov/pubmed/36905061 http://dx.doi.org/10.3390/s23052859 |
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