A survey of brain-inspired intelligent robots: Integration of vision, decision, motion control, and musculoskeletal systems

H Qiao, J Chen, X Huang - IEEE Transactions on Cybernetics, 2021 - ieeexplore.ieee.org
Current robotic studies are focused on the performance of specific tasks. However, such
tasks cannot be generalized, and some special tasks, such as compliant and precise …

An overview of emotion in artificial intelligence

G Assunção, B Patrão… - IEEE Transactions …, 2022 - ieeexplore.ieee.org
The field of artificial intelligence (AI) has gained immense traction over the past decade,
producing increasingly successful applications as research strives to understand and exploit …

Speech emotion recognition based on an improved brain emotion learning model

ZT Liu, Q **e, M Wu, WH Cao, Y Mei, JW Mao - Neurocomputing, 2018 - Elsevier
Human-robot emotional interaction has developed rapidly in recent years, in which speech
emotion recognition plays a significant role. In this paper, a speech emotion recognition …

Integrating feature extraction approaches with hybrid emotional neural networks for water quality index modeling

SI Abba, RA Abdulkadir, SS Sammen, QB Pham… - Applied Soft …, 2022 - Elsevier
The establishment of water quality prediction models is vital for aquatic ecosystems analysis.
The traditional methods of water quality index (WQI) analysis are time-consuming and …

A novel approach for coronary artery disease diagnosis using hybrid particle swarm optimization based emotional neural network

AH Shahid, MP Singh - Biocybernetics and Biomedical Engineering, 2020 - Elsevier
Coronary artery disease (CAD) can cause serious conditions such as severe heart attack,
heart failure, and angina in patients with cardiovascular problems. These conditions may be …

Practical emotional neural networks

E Lotfi, MR Akbarzadeh-T - Neural networks, 2014 - Elsevier
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 …

Memristive circuit implementation of context-dependent emotional learning network and its application in multitask

C Xu, C Wang, J Jiang, J Sun… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
Emotional intelligence plays an important role in artificial intelligence. The brain circuitry of
emotion mainly includes the prefrontal cortex, the amygdala, hippocampus and et al. Many …

Hourly river flow forecasting: application of emotional neural network versus multiple machine learning paradigms

ZM Yaseen, SR Naganna, Z Sa'adi, P Samui… - Water Resources …, 2020 - Springer
Monitoring hourly river flows is indispensable for flood forecasting and disaster risk
management. The objective of the present study is to develop a suite of hourly river flow …

Comparative implementation between neuro-emotional genetic algorithm and novel ensemble computing techniques for modelling dissolved oxygen concentration

SI Abba, RA Abdulkadir, SS Sammen… - Hydrological …, 2021 - Taylor & Francis
Accurate prediction of dissolved oxygen (DO) concentration is important for managing
healthy aquatic ecosystems. This study investigates the comparative potential of the …

Implementing brain-like fear generalization and emotional arousal associated with memory

M Guo, D Zhang, W Guo, G Dou… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Emotion plays an important role in human life. In recent years, memristor-based emotion
circuits have been proposed extensively, but few circuits simulate the neural circuity that …