The field of cognitive dynamic systems (CDSs) is an emerging area of research, whereby engineering learns from neuroscience. Under this framework, engineering systems are configured in a manner that mimics the human brain and improves the utility and performance of traditional systems. In essence, a CDS builds on Fuster’s paradigm of cognition and is fulfilled with the presence of five cognitive processes: the perception-action cycle, memory, attention, intelligence, and language. When augmented with these processes, a system can be classified as a CDS and is afforded the capabilities of processing information and learning from experience through continued interactions with the environment. Tremendous benefit from adopting the CDS framework has been observed in the literature, especially in the fields of cognitive radio and cognitive radar. More recently, the framework has been extended to other areas, such as control theory, risk control, and the Internet of Things; where the potential for drastic performance improvements has been evident in the literature. This comprehensive article presents a thorough background and exposition of the CDS framework and each field where it has been applied. In addition, we provide a comprehensive review of the recent advancements and related works in each domain by summarizing the key facts relating to the methodologies, findings, and limitations of the surveyed papers. Our novel contributions involve being the first source of centralized information on this topic and forming the foundation for future research efforts by presenting suggestions regarding worthwhile avenues for further investigation.

中文翻译：

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认知动态系统：理论、应用和最新进展回顾


认知动态系统（CDS）领域是一个新兴的研究领域，工程学从神经科学中学习。在此框架下，工程系统以模仿人脑的方式进行配置，并提高了传统系统的实用性和性能。本质上，CDS 建立在 Fuster 的认知范式之上，并通过五个认知过程的存在来实现：感知-行动周期、记忆、注意力、智力和语言。当通过这些过程进行增强时，系统可以被归类为 CDS，并具有处理信息和通过与环境持续交互来学习经验的能力。文献中已经观察到采用 CDS 框架带来的巨大好处，特别是在认知无线电和认知雷达领域。最近，该框架已扩展到其他领域，例如控制理论、风险控制和物联网；文献中已经证明了显着提高性能的潜力。这篇内容全面的文章对 CDS 框架及其应用的各个领域进行了全面的背景介绍和阐述。此外，我们通过总结与调查论文的方法、发现和局限性相关的关键事实，对每个领域的最新进展和相关工作进行了全面回顾。我们的新颖贡献包括成为该主题的第一个集中信息来源，并通过提出有关进一步研究的有价值途径的建议，为未来的研究工作奠定基础。