Abstract: This paper investigates the use of relaxed recentered logarithmic barrier functions in the context of nonlinear model predictive control. These functions are a variation of the regular ...

Abstract: This paper proposes energy-efficient approximate multipliers based on the Mitchell’s log multiplication, optimized for performing inferences on convolutional neural networks (CNN). Various ...