In fact, both versions of the new technique outperform by far, in terms of estimation accuracy, the RM estimator with an advantage for version II over version I (the advantage of exploiting the Toeplitz structure is now clearer).
Several computer simulation based experiments are performed to confirm that the proposed methods can reconstruct the original channel coefficient more effectively when compared to the conventional channel estimator in terms of estimation accuracy.
In terms of estimation, conceptually, one can estimate β js in a way analogous to linear reduction, i.e. through the eigen decomposition:, where Σ ϕ= Cov{ ϕ(X)} and Ωϕ is defined similarly as Ω x except we replace X with ϕ(X).
In the finite-dimensional setting, we derive mild sufficient conditions which ensure that a distributed estimator performs better than the local optimal ones in terms of estimation error variance.
We now compare both algorithms in terms of estimation accuracy.
The efficacy of these designs is studied, both in terms of estimation efficiency and discrimination success.
Also, they further consider the same problem in terms of estimation or compensation.
Also, they consider the same problem in terms of estimation or compensation.
Therefore, the proposed TBD algorithm outperforms the benchmark method in terms of estimation accuracy.
Optical design software can be used to assess these virtual surface in terms of estimation and optimization.
