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Discrete optimization is a difficult task common to many different areas in modern research. This type of optimization refers to problems where solution elements can assume one of several discrete values. The most basic form of discrete optimization is bin ...
This paper describes new optimization strategies that offer significant improvements in performance over existing methods for bridge-truss design. In this study, a real-world cost function that consists of costs on the weight of the truss and the number of ...
An analysis of unsupervised neural network models and the use of self-organizing maps in the real-time monitoring of power transformers was carried out. The application of genetic algorithms in a complex optimization problem, the allocation and parameters ...
An efficient hybrid method to optimize the phase states distribution, or phase diagram, of a digitally-reconfigurable reflective cell is presented. It allows minimizing phase quantization errors in applications such as reflect arrays. Digital control of th ...
System-level design decisions such as HW/SW partitioning, target architecture selection and scheduler selection are some of the main concerns of current complex system-on-chip (SOC) designs. In this paper, a novel window-based heuristic is proposed that ad ...
This report presents a new methodological approach for the optimal design of energy integrated batch processes. The main emphasis is put on indirect and, to some extend, on direct heat exchange networks with the possibility of introducing closed or open st ...
Synthetic yet realistic images are valuable for many applications in visual sciences and medical imaging. Typically, investigators develop algorithms and adjust their parameters to generate images that are visually similar to real images. In this study, we ...
We present a new approach that is able to produce an increased fault tolerance in bio-inspired electronic circuits. In order to do so, we designed hardware-friendly genetic regulatory networks based on a bio-inspired hardware architecture called POEtic tis ...
Matching pursuit decomposes a signal into a linear expansion of functions selected from a redundant dictionary, isolating the signal structures that are coherent with respect to a given dictionary. In this paper we focus on the Matching Pursuit representat ...
Matching Pursuit decomposes a signal into a linear expansion of functions selected from a redundant dictionary, isolating the signal structures that are coherent with respect to a given dictionary. In this paper we focus on the Matching Pursuit representat ...