Sentence examples for blind sensing from inspiring English sources

Blind sensing techniques thus operate ideally in scenarios of stationary noise, whereas in practice [30] most of the noise turns out to be non-stationary (i.e., noise uncertainty).

We select an example of feature spectrum sensing algorithms, the CD detector, and an example of blind sensing algorithms, the ED detector.

Special attention has been paid to blind sensing methods that do not need information of the source signals and the propagation channels.

According to the a priori information required to detect the primary user and the resulting complexity and accuracy, general spectrum sensing techniques can be categorized in the following types: blind sensing and feature-based sensing techniques.

In addition, recently a blind sensing spectrum technique has been introduced based on the wavelet transform which is able to deliver spectrum estimation over a wide-band of frequencies [43, 44].

Moreover, different experimental results indicate that the blind sensing detector can achieve high detection probability at a low false alarm probability under real channel conditions and low signal-to-noise ratio.

The emperor's blind sense of omnipotence translates well into the way Coote effortlessly wrests control away from the pit, slowing the orchestra – at times almost to a standstill – and the way she both inhabits the character as well as exceeds it, revelling in the electricity of her vocal presence.

Unless, of course, you feel obligated to pay more than your fair share in Federal income tax or are compelled by a blind sense of duty to give Uncle Sam a good chunk of your money interest free for a year.

Various judges and juries have, in fact, shown themselves to be unfazed by both public and governmental pressures and have, in terror and national security cases, demonstrated signs of balance and of a concern for justice, rather than being driven by a blind sense of revenge.

The second paper, "Efficient blind spectrum sensing for cognitive radio networks based on compressed sensing" by Shancang Li, Xinheng Wang, and Xu Zhou, proposes to improve signal reconstruction algorithms by using ℓp-norm (0 < p < 1) minimization instead of ℓ1 or ℓ1/ℓ2 mixed minimization that are commonly used in existing signal recovery schemes.

Recently, a new blind spectrum sensing technique based on the sparse property of the cyclic autocorrelation function (CAF) was developed for sensing the spectrum holes in the primary users' bands.