Sentence examples for memory components and from inspiring English sources

Prof. Liu will also explore possible applications of spin orbitronic devices both as memory components and logic devices.

Standard information criteria for selecting cointegrating rank are shown to be weakly consistent in semiparametric RRR models in which the errors have general nonparametric short memory components and shifting volatility provided the penalty coefficient Cn → infinity and Cn/n → 0 as n → ∞.

Based on these reports from Kuo and others, the company is looking to dramatically decrease physical material costs, which are relatively stable compared to the cost of processor and flash memory components, and tooling/factory setup, which decrease as a production process matures.

RCA, for example, built the inner memory component and the "Selectron" tube.

Allowing for a nonparametric short memory component and using a reduced rank regression with only a single lag, standard information criteria are shown to be weakly consistent in the choice of cointegrating rank provided the penalty coefficient Cn → ∞ and Cn/n → 0 as n → ∞.

However, the deselect current is partly present in vendor data sheets to keep track of signal line toggling during idle periods of a memory component and therefore supported by our model.

This action of stopping is the best index of the prospective memory component and the least confounded by retrospective memory ability to recollect the content of the plan.

The number of counted ticks is then compared in working memory to those previously stored in a reference memory to establish a match (memory component), and thereby make a decision about the duration of the interval (decision component).

Theoretical capacity taking into account the capacity of the memory component and the number of bytes to save for measurement, but may not be achieved due to battery life.

In most cases, girls showed higher performance on scale components than boys, with significantly higher scores for perceptual-performance at 42 months and for the GCI, verbal, and memory components at 42 and 48 months.

In particular, by analysing the utilization of graphics and memory components at a single voltage and frequency levels, the proposed classification methodologies are able to predict the impact of DVFS on GPGPU applications execution time and power and energy consumption.