AbstractWe will construct new classes of Parseval frames for a Hilbert space which allow signal reconstruction from the absolute value of the frame coefficients. As a consequence, signal reconstruction can be done without using phase or its estimation. This verifies a longstanding conjecture of the speech processing community
In our earlier work, we have measured human intelligibility of stimuli reconstructed either from the...
Abstract. We consider signal reconstruction from the norms of subspace components generalizing stand...
We consider signal reconstruction from the norms of subspace components generalizing standard phase ...
We will construct new classes of Parseval frames for a Hilbert space which allow signal reconstructi...
AbstractWe will construct new classes of Parseval frames for a Hilbert space which allow signal reco...
We derive fast algorithms for doing signal reconstruction without phase. This type of problem is imp...
Frame design for phaseless reconstruction is now part of the broader problem of nonlinear recon- str...
In this paper we present a signal reconstruction algorithm from absolute value of frame coefficients...
Abstract. The primary goal of this paper is to develop fast algorithms for signal reconstruction fro...
It is well known that the phase of the Fourier transform of a signal contains a significant amount o...
Abstract The goal of this paper is to develop fast algorithms for signal reconstruc-tion from magnit...
The goal of this paper will be to study how frame theory is applied within the field of signal proce...
In general, reconstruction of a speech signal from the spectrogram is non-unique because of the unav...
Besides basis expansions, frames representations play a key role in signal processing. We thus consi...
Single-channel speech separation algorithms frequently ignore the issue of accurate phase estimation...
In our earlier work, we have measured human intelligibility of stimuli reconstructed either from the...
Abstract. We consider signal reconstruction from the norms of subspace components generalizing stand...
We consider signal reconstruction from the norms of subspace components generalizing standard phase ...
We will construct new classes of Parseval frames for a Hilbert space which allow signal reconstructi...
AbstractWe will construct new classes of Parseval frames for a Hilbert space which allow signal reco...
We derive fast algorithms for doing signal reconstruction without phase. This type of problem is imp...
Frame design for phaseless reconstruction is now part of the broader problem of nonlinear recon- str...
In this paper we present a signal reconstruction algorithm from absolute value of frame coefficients...
Abstract. The primary goal of this paper is to develop fast algorithms for signal reconstruction fro...
It is well known that the phase of the Fourier transform of a signal contains a significant amount o...
Abstract The goal of this paper is to develop fast algorithms for signal reconstruc-tion from magnit...
The goal of this paper will be to study how frame theory is applied within the field of signal proce...
In general, reconstruction of a speech signal from the spectrogram is non-unique because of the unav...
Besides basis expansions, frames representations play a key role in signal processing. We thus consi...
Single-channel speech separation algorithms frequently ignore the issue of accurate phase estimation...
In our earlier work, we have measured human intelligibility of stimuli reconstructed either from the...
Abstract. We consider signal reconstruction from the norms of subspace components generalizing stand...
We consider signal reconstruction from the norms of subspace components generalizing standard phase ...
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