TY - JOUR
T1 - Error reconstruction functions of non-optimal algorithms based on atomic functions
AU - Olvera, Yair
AU - Kazakov, Vladimir
AU - Africanov, Sviatoslav
N1 - Publisher Copyright:
© 2016, North Atlantic University Union. All rights reserved.
PY - 2016
Y1 - 2016
N2 - A non-optimal algorithm based on atomic function is investigated for the Sampling-Reconstruction Procedure (SRP) of Gaussian random process realizations. The reconstruction error function of this non-optimal algorithm is compared with the reconstruction error functions obtained in the optimal algorithm, represented by the conditional mean rule, and in another non-optimal algorithm based on Balakrishnan’s theorem. Results show that the application of atomic functions has disadvantages reflected in a larger magnitude of the reconstruction error.
AB - A non-optimal algorithm based on atomic function is investigated for the Sampling-Reconstruction Procedure (SRP) of Gaussian random process realizations. The reconstruction error function of this non-optimal algorithm is compared with the reconstruction error functions obtained in the optimal algorithm, represented by the conditional mean rule, and in another non-optimal algorithm based on Balakrishnan’s theorem. Results show that the application of atomic functions has disadvantages reflected in a larger magnitude of the reconstruction error.
KW - Atomic functions
KW - Conditional mean rule
KW - Non-optimal algorithm
KW - Reconstruction error function
UR - http://www.scopus.com/inward/record.url?scp=84975527193&partnerID=8YFLogxK
M3 - Artículo
SN - 1998-0159
VL - 10
SP - 302
EP - 309
JO - International Journal of Mathematics and Computers in Simulation
JF - International Journal of Mathematics and Computers in Simulation
ER -