Sentence examples for processing capable from inspiring English sources

The results demonstrate that the magnocellular information undergoes processing capable of detecting differences in the sequence of unattended peripheral motion stimuli.

To meet the huge demand of nanostructured silicon, a growing number of research teams are active to find new strategies and develop high-output batch processing capable of producing nanostructured silicon powder in quantities allowing upscaling to industrial demands[16 18].

In recent years, Wireless Sensor Networks have experienced significant growth, mainly motivated by the development of standard communication protocols and the availability of low cost microcontrollers and wireless transceivers, resulting in low-power small-size sensing and data processing capable devices, and wireless communication links.

When creating a PANU, one obtains a data processing component capable of simulating the operation of a biological neuron.

Chemical reaction-diffusion media represent information effective processing means capable of solving problems of high computational complexity.

In contrast, BN processing is capable of further improving the ASR performances for both feature types, meanwhile, reducing the feature dimension particularly for AMFB features.

In this work we propose a signal processing technique capable of identifying and characterizing the number of capacitor banks connected to a standard North-American feeder circuit.

Several processing algorithms capable of suppressing grain noise have been proposed, of which the split spectrum processing (SSP) probably is the most renowned.

Tissue and biomedical engineering fields are in constant mutation and in searching for innovative processing techniques capable to tailor the material properties.

Its implementation is based on specific image processing algorithms capable of predicting human regions-of-interest, ROIs, and on a corresponding differentiated quantization of the DCT coefficients.

Much research is currently devoted to developing automatic image processing systems capable of determining the level of sleepiness based on characteristics such as facial tone, slow eyelid closure, rubbing, yawning and nodding [35, 36, 37, 38, 39].