title: Practical emotional neural networks.
abstract: In this paper, we propose a limbic-based artificial emotional neural network (LiAENN) for a pattern recognition problem. LiAENN is a novel computational neural model of the emotional brain that models emotional situations such as anxiety and confidence in the learning process, the short paths, the forgetting processes, and inhibitory mechanisms of the emotional brain. In the model, the learning weights are adjusted by the proposed anxious confident decayed brain emotional learning rules (ACDBEL). In engineering applications, LiAENN is utilized in facial detection, and emotion recognition. According to the comparative results on ORL and Yale datasets, LiAENN shows a higher accuracy than other applied emotional networks such as brain emotional learning (BEL) and emotional back propagation (EmBP) based networks.
authors: Department of Computer Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran. Electronic address: esilotf@gmail.com.
authors: Ehsan
authors: E
authors: Lotfi
authors: Department of Electrical and Computer Engineering, Center of Excellence on Soft Computing and Intelligent Information Processing, Ferdowsi University of Mashhad, Iran. Electronic address: akbazar@um.ac.ir.
authors: M-R
authors: MR
authors: Akbarzadeh-T
mesh_terms: D000818:Animals; D004644:Emotions / Q000502:physiology*; D006801:Humans; D008032:Limbic System / Q000502:physiology; D008959:Models, Neurological; D009415:Nerve Net / Q000502:physiology*
keywords: Amygdala; BELBIC; Cognition; Emotion; Emotional state; Learning