Neural networks have become instrumental in advancing computer engineering by drawing insights from cognitive psychology. This research article explores the synergy between neural network models and cognitive psychology theories, highlighting how computational models simulate human cognitive processes. By integrating principles of memory, learning, and decision-making from cognitive psychology, neural networks emulate complex human behaviors and intelligence. The article reviews current methodologies and case studies to illustrate the application of neural networks in solving engineering challenges, such as pattern recognition, natural language processing, and autonomous systems. Ethical considerations and future directions for enhancing neural network capabilities through cognitive psychology are also discussed, emphasizing the transformative impact of this interdisciplinary approach on computer engineering and cognitive science research.
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