Many perceptual processes and neural computations, such as speech recognition, motor control and learning, depend on the ability to measure and mark the passage of time. However, ...
Artificial Neural Networks for online learning problems are often implemented with synaptic plasticity to achieve adaptive behaviour. A common problem is that the overall learning...
: A series of hypotheses is proposed, connecting neural structures and dynamics with the formal structures and processes of probabilistic logic. First, a hypothetical connection is...
This case study demonstrates how the synthesis and the analysis of minimal recurrent neural robot control provide insights into the exploration of embodiment. By using structural e...
The neural computations that support bat echolocation are of great interest to both neuroscientists and engineers, due to the complex and extremely time-constrained nature of the ...
Cricket females perform phonotaxis towards the specific sounds produced by male crickets. By means of a well-tuned peripheral auditory system the cricket is able to extract direct...
Ben Torben-Nielsen, Barbara Webb, Richard E. Reeve
In this paper, a user-centred innovative method of knowledge extraction in neural networks is described. This is based on information visualization techniques and tools for artific...
— This paper considers the problem of PD control of overhead crane in the presence of uncertainty associated with crane dynamics. By using radial basis function neural networks, ...
The brain has long been seen as a powerful analogy from which novel computational techniques could be devised. However, most artificial neural network approaches have ignored the...
Gul Muhammad Khan, Julian F. Miller, David M. Hall...
Abstract. We present a model of a recurrent neural network with homeostasic units, embodied in a minimalist articulated agent with a single link and joint. The configuration of th...