TY - JOUR
T1 - Identificador con comparación entre dos estimadores
AU - Medel Juárez, J. J.
AU - García Infante, J. C.
AU - Urbieta Parrazales, R.
PY - 2011
Y1 - 2011
N2 - This paper describes the identification process as an adaptive digital filter using the estimated transition matrix, identification error and gain functions. One problem that the filter has is the time process, affecting the quality response and agreeing with the estimated transition function, which is a condition to be accomplished with respect to the reference time evolution system. Thus, the time process required must be met in all operations within the same time interval. Generally, the identifier filter answer is affected by the parameter used in the estimated transition function indirectly used in the other filter operations. In this case, seeking a better time estimation response two estimators were considered: the first expressed in a recursive form and the second, selected within the knowledge base gain used in accordance to fuzzy logic. The results show the convergence observed in the error differences and their approximations to the stochastic time model conditions with k samples, using, MatLab® as a simulation software.
AB - This paper describes the identification process as an adaptive digital filter using the estimated transition matrix, identification error and gain functions. One problem that the filter has is the time process, affecting the quality response and agreeing with the estimated transition function, which is a condition to be accomplished with respect to the reference time evolution system. Thus, the time process required must be met in all operations within the same time interval. Generally, the identifier filter answer is affected by the parameter used in the estimated transition function indirectly used in the other filter operations. In this case, seeking a better time estimation response two estimators were considered: the first expressed in a recursive form and the second, selected within the knowledge base gain used in accordance to fuzzy logic. The results show the convergence observed in the error differences and their approximations to the stochastic time model conditions with k samples, using, MatLab® as a simulation software.
KW - Algorithms for functional approximation
KW - Artificial intelligence
KW - Computer modeling and simulation
KW - Fuzzy logic
KW - Stochastic processes
UR - http://www.scopus.com/inward/record.url?scp=84857865524&partnerID=8YFLogxK
M3 - Artículo
SN - 0035-001X
VL - 57
SP - 414
EP - 420
JO - Revista Mexicana de Fisica
JF - Revista Mexicana de Fisica
IS - 5
ER -