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A survey of brain-inspired intelligent robots: Integration of vision, decision, motion control, and musculoskeletal systems
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 …
tasks cannot be generalized, and some special tasks, such as compliant and precise …
An overview of emotion in artificial intelligence
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 …
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 …
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
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 …
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
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 …
heart failure, and angina in patients with cardiovascular problems. These conditions may be …
Practical emotional neural networks
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 …
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 …
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
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 …
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
Accurate prediction of dissolved oxygen (DO) concentration is important for managing
healthy aquatic ecosystems. This study investigates the comparative potential of the …
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 …
circuits have been proposed extensively, but few circuits simulate the neural circuity that …