Projecte llegit
Títol: Programación eficiente de algoritmos de estimación de parámetros para modelado de amplificadores de RF
Estudiants que han llegit aquest projecte:
- BHAMBI BLANCO, RAHUL (data lectura: 25-07-2017)
- Cerca aquest projecte a Bibliotècnica
Director/a: MONTORO LÓPEZ, GABRIEL
Departament: TSC
Títol: Programación eficiente de algoritmos de estimación de parámetros para modelado de amplificadores de RF
Data inici oferta: 01-02-2017 Data finalització oferta: 01-10-2017
Estudis d'assignació del projecte:
- GR ENG SIS TELECOMUN
- GR ENG TELEMÀTICA
Tipus: Individual | |
Lloc de realització: EETAC | |
Segon director/a (UPC): GILABERT PINAL, PERE LLUÍS | |
Paraules clau: | |
predistorsión | |
Descripció del contingut i pla d'activitats: | |
Programación eficiente de algoritmos de estimación de parámetros para modelado y predistorsión digital de amplificadores de RF | |
Overview (resum en anglès): | |
An adaptive filter is a device that attempts to model the relationship between signals in real time in an iterative way.
Among all the adaptive filters, the most outstanding among them is the Least Mean Square (LMS). Least Mean Square was created in 1960 by Professor Bernand Widrow and his student Ted Hoff. Least Mean Square is used to calculate the coefficients from the desired output signal with the output signal that we obtain from the coefficients that we have calculated. The LMS has several ways to get its coefficients: LMS, NLMS, Sign-LMS, etc. NLMS, normalize the input signal when we calculate coefficients and the Sign-LMS from the input signal, when calculating the coefficients and Sign-LMS from the input signal, error or both at once, where if the number is positive we will give value equal to 1 and if we obtain a negative number, the value is -1. With each form of LMS, we can see who is the fastest when it comes to obtaining coefficients or we can also which one has the least error. |