Fifty years ago, the optimization of thermoelectric devices was analyzed by considering the relation between optimal performances and local entropy production. Entropy is produced by the irreversible processes in thermoelectric devices. If these processes could be eliminated, entropy production would be reduced to zero, and the limiting Carnot efficiency or coefficient of performance would be o...

Differential entropy is a quantity used in many signal processing problems. Often we need to calculate not only the entropy itself, but also its gradient with respect to various variables, for efficient optimization, sensitivity analysis, etc. Entropy estimation can be based on an estimate of the probability density function, which is computationally costly if done naively. Some prior algorithm...

In this paper, we show the results of applying stochastic sampling methods such as Cross Entropy method and Sampling Based Differential Dynamic Programming method to path planning of Unmanned Ground Vehicles (UGV) on unstructured 3D terrains. We show the superiority of sampling algorithms to local optimization methods such as Gauss Newton optimization method through simulations.A high fidelity ...

Clustering is a fundamental tool for exploratory data analysis. Information theoretic clustering is based on the optimization of information theoretic quantities such as entropy and mutual information. Recently, since these quantities can be estimated in non-parametric manner, non-parametric information theoretic clustering gains much attention. Assuming the dataset is sampled from a certain cl...