Sökning: "Miguel de"
Visar resultat 6 - 10 av 23 avhandlingar innehållade orden Miguel de.
6. Traducción y creación : tres poetas traductores colombianos del siglo XX: Jaime Tello, José Manuel Arango y Harold Alvarado Tenorio
Sammanfattning : Este trabajo realiza un análisis crítico de las elecciones traductivas —elecciones del poeta traductor en su re-poetización— de tres poetas traductores colombianos de mediados del siglo XX. El objetivo de esta tesis es analizar las poéticas de la traducción de Jaime Tello, José Manuel Arango y Harold Alvarado Tenorio, con el fin de contribuir a la historiografía de la traducción de poesía en Colombia. LÄS MER
7. Enhancing Differential Evolution Algorithm for Solving Continuous Optimization Problems
Sammanfattning : Differential Evolution (DE) has become one of the most important metaheuristics during the recent years, obtaining attractive results in solving many engineering optimization problems. However, the performance of DE is not always strong when seeking optimal solutions. It has two major problems in real world applications. LÄS MER
8. IMPROVING DIFFERENTIAL EVOLUTION WITH ADAPTIVE AND LOCAL SEARCH METHODS
Sammanfattning : Differential Evolution (DE) is a population-based algorithm that belongs to the Evolutionary algorithm family. During recent years, DE has become a popular algorithm in optimization due to its strength solving different types of optimization problems and due to its easy usage and implementation. LÄS MER
9. System Identification with Multi-Step Least-Squares Methods
Sammanfattning : The purpose of system identification is to build mathematical models for dynam-ical systems from experimental data. With the current increase in complexity of engineering systems, an important challenge is to develop accurate and computa-tionally simple algorithms, which can be applied in a large variety of settings. LÄS MER
10. Learning flow functions : architectures, universal approximation and applications to spiking systems
Sammanfattning : Learning flow functions of continuous-time control systems is considered in this thesis. The flow function is the operator mapping initial states and control inputs to the state trajectories, and the problem is to find a suitable neural network architecture to learn this infinite-dimensional operator from measurements of state trajectories. LÄS MER