Tsvi G. Dvorkind

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A dual-step approach for speaker localization based on a microphone array is addressed in this paper. In the first stage, which is not the main concern of this paper, the time difference between arrivals of the speech signal at each pair of microphones is estimated. These readings are combined in the second stage to obtain the source location. In this(More)
We treat the problem of reconstructing a signal from its nonideal samples where the sampling and reconstruction spaces as well as the class of input signals can be arbitrary subspaces of a Hilbert space. Our formulation is general, and includes as special cases reconstruction from finitely many samples as well as uniform-sampling of continuous-time signals,(More)
We study a sampling setup where a continuous-time signal is mapped by a memoryless, invertible and nonlinear transformation, and then sampled in a nonideal manner. Such scenarios appear, for example, in acquisition systems where a sensor introduces static nonlinearity, before the signal is sampled by a practical analog-to-digital converter. We develop the(More)
Many sources of information are of analog or continuous-time nature. However, digital signal processing applications rely on discrete data. We consider the problem of approximating L<sub>2</sub> inner products, i.e., representation coefficients of a continuous-time signal, from its generalized samples. Adopting a robust approach, we process these(More)
We address a sampling problem in which the goal is to approximate a signal from its nonideal (generalized) samples. The reconstruction is constrained to lie in a subspace, and to be consistent with the measured samples. It is well known how to obtain a consistent approximation, if the sampling and reconstruction spaces satisfy a certain direct sum(More)
Determining the spatial position of a speaker finds a growing interest in video conference scenario where automated camera steering and tracking are required. As a preliminary step for the localization, microphone array can be used to extract the time difference of arrival (TDOA) of the speech signal. The direction of arrival of the speech signal is then(More)
We consider non-ideal sampling and reconstruction schemes in which the sampling and reconstruction spaces as well as the input signal can be arbitrary. To obtain a good reconstruction of the signal in the reconstruction space from arbitrary samples, we suggest processing the samples prior to reconstruction with a linear transformation that is designed to(More)