Measurement design for detecting sparse signals
نویسندگان
چکیده
منابع مشابه
Measurement design for detecting sparse signals
We consider the problem of testing for the presence (or detection) of an unknown sparse signal in additive white noise. Given a fixed measurement budget, much smaller than the dimension of the signal, we consider the general problem of designing compressive measurements to maximize the measurement signal-to-noise ratio (SNR), as increasing SNR improves the detection performance in a large class...
متن کاملInnovated Higher Criticism for Detecting Sparse Signals in Correlated Noise
Higher Criticism is a method for detecting signals that are both sparse and weak. Although first proposed in cases where the noise variables are independent, Higher Criticism also has reasonable performance in settings where those variables are correlated. In this paper we show that, by exploiting the nature of the correlation, performance can be improved by using a modified approach which expl...
متن کاملTight Measurement Bounds for Exact Recovery of Structured Sparse Signals
Standard compressive sensing results state that to exactly recover an s sparse signal in R, one requires O(s·log p) measurements. While this bound is extremely useful in practice, often real world signals are not only sparse, but also exhibit structure in the sparsity pattern. We focus on group-structured patterns in this paper. Under this model, groups of signal coefficients are active (or ina...
متن کاملSudocodes – Fast Measurement and Reconstruction of Sparse Signals
Sudocodes are a new scheme for lossless compressive sampling and reconstruction of sparse signals. Consider a sparse signal x ∈ R containing only K N non-zero values. Sudo-encoding computes the codeword y ∈ R via the linear matrix-vector multiplication y = Φx, with K < M N . We propose a non-adaptive construction of a sparse Φ comprising only the values 0 and 1; hence the computation of y invol...
متن کاملPhase Retrieval for Sparse Signals
The aim of this paper is to build up the theoretical framework for the recovery of sparse signals from the magnitude of the measurement. We first investigate the minimal number of measurements for the success of the recovery of sparse signals without the phase information. We completely settle the minimality question for the real case and give a lower bound for the complex case. We then study t...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Physical Communication
سال: 2012
ISSN: 1874-4907
DOI: 10.1016/j.phycom.2011.09.007