Sentence examples for acquisition throughput from inspiring English sources

The average acquisition throughput is obtained as T_{text{CS}}^{text{(A)}} = frac{K}{beta_{text{CS}}^{text{(A)}}}.

This increases the acquisition throughput and reduces the jitter sensitivity [14] (jitter refers to link frequency deviations among tags).

The average acquisition throughput is obtained as T_{text{FSA}}^{text{(A)}} = frac{K}{beta_{text{FSA}}^{text{(A)}}} = frac{T_{text{ps}}}{16}.

We observe that with the proposed approach, we can shorten the signatures and thereby drastically increase the acquisition throughput of the CS-RFID schemes.

Fig. 8 Acquisition throughput parameterized on M. With the newly employed BASSAMP algorithm and the exploitation of multiple receive antennas, the maximum acquisition throughput of CS-based schemes can be improved drastically by reducing the sequence length M (or equivalently, the measurement multiplier c).

The Data Acquisition system for the KLOE experiment, presently running at the Laboratori Nazionali di Frascati DAΦNE collider, has been designed to sustain an acquisition throughput of 50 Mbyte/s for an event rate of 10 kHz.

This paper presents a high data throughput acquisition system for pixel detector readout such as CMOS imagers.

Thus subblock parallelism with initialization by acquisition encounters a throughput ceiling value and the maximum speedup (obtained when equals ) is roughly equal to (by neglecting ).

3D US, for instance, has been shown capable of shortening examination times, with faster data acquisition and faster throughput of patients.

Indeed, whilst both ex vivo MRI and micro CT have been applied to the study of murine atherosclerosis, they offer limited resolution, even in relatively large arteries and require long acquisition times limiting throughput [3], [5].

Challenges identified in the Framingham Heart Study include data acquisition (e.g., throughput, cost, and sample tracking/batch effects), storage (e.g., results, storage demands, raw data in one place for cross-comparison, etc)., and limitations with data processors, competing needs on servers, costly renewal of outdated resources, and security issues.