In this work an improvement of an initial approach to design Artificial Neural Networks to forecast Time Series is tackled, and the automatic process to design Artificial Neural N...
The covariance matrix adaptation evolution strategy (CMAES) has proven to be a powerful method for reinforcement learning (RL). Recently, the CMA-ES has been augmented with an ada...
— In recent years, several approaches have been proposed aiming the optimal joint design of finite impulse response (FIR) multiple-input multiple-output (MIMO) transmitter and r...
In the Sesame framework, we develop a modeling and simulation environment for the efficient design space exploration of heterogeneous embedded systems. Since Sesame recognizes se...
In this paper, we present an architecture exploration methodology for low-end embedded systems where the reduction of cost is a primary design concern. The architecture exploratio...