Sparse Phase Retrieval from Short-Time Fourier Measurements
نویسندگان
چکیده
منابع مشابه
A Least Squares Approach for Stable Phase Retrieval from Short-Time Fourier Transform Magnitude
We address the problem of recovering a signal (up to global phase) from its short-time Fourier transform (STFT) magnitude measurements. This problem arises in several applications, including optical imaging and speech processing. In this paper we suggest three interrelated algorithms. The first algorithm estimates the signal efficiently from noisy measurements by solving a simple least-squares ...
متن کاملASR on speech reconstructed from short-time fourier phase spectra
In our earlier papers [1, 2], we have measured human intelligibility of speech stimuli reconstructed either from the short-time magnitude spectra (magnitude-only stimuli) or the short-time phase spectra (phase-only stimuli) of a speech stimulus. We demonstrated that, even for small analysis window durations of 20-40 ms (of relevance to automatic speech recognition), the short-time phase spectru...
متن کاملSparse Signal Reconstruction from Phase-only Measurements
We demonstrate that the phase of complex linear measurements of signals preserves significant information about the angles between those signals. We provide stable angle embedding guarantees, akin to the restricted isometry property in classical compressive sensing, that characterize how well the angle information is preserved. They also suggest that a number of measurements linear in the spars...
متن کاملOn Sparse Reconstruction from Fourier and Gaussian Measurements
This paper improves upon best-known guarantees for exact reconstruction of a sparse signal f from a small universal sample of Fourier measurements. The method for reconstruction that has recently gained momentum in the sparse approximation theory is to relax this highly nonconvex problem to a convex problem and then solve it as a linear program. We show that there exists a set of frequencies su...
متن کاملFast Phase Retrieval from Local Correlation Measurements
We develop a fast phase retrieval method which can utilize a large class of local phaseless correlationbased measurements in order to recover a given signal x ∈ C (up to an unknown global phase) in near-linear O ( d log d ) -time. Accompanying theoretical analysis proves that the proposed algorithm is guaranteed to deterministically recover all signals x satisfying a natural flatness (i.e., non...
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: IEEE Signal Processing Letters
سال: 2015
ISSN: 1070-9908,1558-2361
DOI: 10.1109/lsp.2014.2364225