On the Fundamental Limits of Adaptive Sensing

Details On the Fundamental Limits of Adaptive Sensing On the Fundamental Limits of Adaptive Sensing

2011-11-20

arxiv.org/abs/1111.4646v2

Mathematics

Statistics Theory

Scientific paper

Suppose we can sequentially acquire arbitrary linear measurements of an n-dimensional vector x resulting in the linear model y = Ax + z, where z represents measurement noise. If the signal is known to be sparse, one would expect the following folk theorem to be true: choosing an adaptive strategy which cleverly selects the next row of A based on what has been previously observed should do far better than a nonadaptive strategy which sets the rows of A ahead of time, thus not trying to learn anything about the signal in between observations. This paper shows that the folk theorem is false. We prove that the advantages offered by clever adaptive strategies and sophisticated estimation procedures---no matter how intractable---over classical compressed acquisition/recovery schemes are, in general, minimal.

Affiliated with

Also associated with

No associations

Rating

On the Fundamental Limits of Adaptive Sensing does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with On the Fundamental Limits of Adaptive Sensing, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and On the Fundamental Limits of Adaptive Sensing will most certainly appreciate the feedback.

Rate now

Comments { 0 }

Profile ID: LFWR-SCP-O-130269