Sentence examples for tracking scheme to from inspiring English sources

Section 3 applies the proposed FOSB tracking scheme to overcome the computational complexity of the traditional tracking scheme.

In this section, we introduce a novel subblock tracking scheme to alleviate the computational burden of the data detection in doubly selective environment.

Since TeTraKron allows us to extend an arbitrary matrix-based subspace tracking scheme to the tensor case, we choose two examples, namely, the simple but widely used PAST algorithm [7] as well as the FAPI scheme [6] that is a fast implementation of the power iteration method for subspace tracking.

We show the corresponding numerical results in Section 5. To summarize, in case that forward-backward-averaging is incorporated, the TeTraKron framework can be employed to extend a matrix-based subspace tracking scheme to tensors such that real-valued tensor-based subspace tracking is realized.

TeTraKron allows to extend arbitrary matrix-based subspace tracking schemes to track the tensor-based subspace estimate.

TeTraKron allows to extend arbitrary existing matrix-based subspace tracking schemes to the tracking of the HOSVD-based subspace estimate.

Consequently, the TeTraKron framework enables the extension of matrix-based subspace tracking schemes to realize real-valued tensor-based subspace tracking where forward-backward-averaging is included and provides benefits in terms of both the performance and the complexity.

TeTraKron allows to exploit the rich heritage of matrix-based subspace tracking and flexibly extends arbitrary matrix-based subspace tracking schemes to the tracking of the HOSVD-based subspace estimate defined in [10] by running them on all the unfoldings of the data tensor in parallel.

TeTraKron allows to readily extend arbitrary matrix-based subspace tracking schemes to tensors which yields an improved estimation accuracy as we demonstrate in Section 5. Therefore, we obtain novel tensor-based subspace trackers by building on known algorithms, which is a particularly attractive feature of the TeTraKron framework.

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