Sentence examples for uncertainty spectrum from inspiring English sources

Another method is interval optimization [33], in which confidence intervals in terms of upper and lower bounds are used to represent the uncertainty spectrum.

Instead of assuming it is, shouldn't we try to understand where on the uncertainty spectrum we fall: conscientiously ambivalent or riddled with doubt?

Successful resource allocation in CR systems has to overcome the uncertainty of spectrum bands availability as well as the chaotic wireless propagation environment.

The threshold λ is determined by the constraint on p fa and reflects the effect of noise uncertainty on spectrum sensing.

The DS method proposed here has this capability: by showing a high level of uncertainty, the spectrum manager knows there is insufficient coverage in this area and can make decisions accordingly.

A new chiller sizing method is proposed in this paper taking into account the scenario parameter uncertainty, the discrete spectrum of nominal cooling capacity of available chillers, the difference of chiller cooling capacity under nominal condition and peak cooling load condition.

Entropy-based detection can solve the noise uncertainty of the spectrum sensing through information entropy.

However, although all of the aforementioned studies consider some realistic constraints, they apply to the traditional wireless multi-hop networks only and do not consider the spectrum uncertainty in CRNs.

More conclusive measures and findings stem from our ability to assess uncertainty across the spectrum of legacy data in relation to more recent HRT data using techniques like we have documented in this research.

Results given in Section 8 show that when the exact uncertainty in the spectrum domain is known, recognition results with the suggested approach are far in excess of those achievable by ICA alone.

Estimating the uncertainty in the spectrum domain has clear advantages, when contrasted with uncertainty estimation in the domain of speech recognition, since much intermediate information about the signal and noise process as well as the mask is known in this phase of signal processing, but is generally not available in the further steps of feature extraction.