Biological intelligence processes information using impulses or spikes, which makes those
living creatures able to perceive and act in the real world exceptionally well and outperform …

Combined efforts in the fields of neuroscience, computer science, and biology allowed to
design biologically realistic models of the brain based on spiking neural networks. For a …

Learning-based methods have demonstrated clear advantages in controlling robot tasks,
such as the information fusion abilities, strong robustness, and high accuracy. Meanwhile …

Spiking neural networks are in theory more computationally powerful than rate-based neural
networks often used in deep learning architectures. However, unlike rate-based neural …

Spiking neural networks (SNNs) offer many advantages over traditional artificial neural
networks (ANNs) such as biological plausibility, fast information processing, and energy …

Building spiking neural networks (SNNs) based on biological synaptic plasticities holds a
promising potential for accomplishing fast and energy-efficient computing, which is …

传统机器人经过长时间的研究和发展, 已经在生产和生活的多个领域得到了广泛的应用,
但在复杂多变的环境中依然缺乏与真实生物类似的灵活性, 稳定性和适应能力 …

Traditionally, human vision research has focused on specific paradigms and proposed
models to explain very specific properties of visual perception. However, the complexity and …

Collective endeavours in the fields of computational neuroscience, software engineering,
and biology permitted outlining naturally sensible models of the human brain in light of …

Studying the underlying mechanism of neural circuit and modelling it to control locomotion
remains non-trivial. This thesis presents a biological-inspired hierarchical control …