NeuroSCA: Evolving Activation Functions for Side-Channel Analysis

The choice of activation functions can significantly impact the performance of neural networks. Due to an ever-increasing number of new activation functions being proposed in the literature, selecting the appropriate activation function becomes even more difficult. Consequently, many researchers approach this problem from a different angle, in...

Evolved Neuromorphic Control for High Speed Divergence-based Landings of MAVs

Flying insects are capable of autonomous vision-based navigation in cluttered environments, reliably avoiding objects through fast and agile manoeuvres. Meanwhile, insect-scale micro air vehicles still lag far behind their biological counterparts, displaying inferior performance at a fraction of the energy efficiency. In light of this, it is in...

Low-Thrust Gravity Assist Trajectory Optimisation using Evolutionary Neurocontrol

With all major bodies within the Solar System explored by at least a single fly-by, modern-day missions are becoming increasingly more demanding, up to a point where classical chemical propulsion can no longer supply the required ∆V. Increasingly more is relied upon low-thrust propulsion, characterised by its (very) low thrust force; long...