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The SAMPL Lab at the Weizmann Institute of Science offers a postdoctoral position within the project C'MON-QSENS! (Continuously Monitored Quantum Sensors: Smart Tools and Applications) funded by QuantERA EU program in Quantum Technologies. The appointment will be for a two years term, (possibly) renewable for a third year.
The SAMPL Lab at the Weizmann Institute of Science offers a postdoctoral position within the project C'MON-QSENS! (Continuously Monitored Quantum Sensors: Smart Tools and Applications) funded by QuantERA EU program in Quantum Technologies. The appointment will be for a two years term, (possibly) renewable for a third year.
PhD students and Postdocs in the areas of signal processing, machine learning, medical imaging, communications and radar processing:
Host Professor: Yonina Eldar, department of mathematics and computer science, Weizmann Institute
Active control of noise for multi-channel applications is affected by the existence of nonlinear primary and secondary paths. There is a degradation in the performance of linear multi-channel active noise control (LMANC) systems based on minimization of sum of squared errors obtained from multiple sensors in presence of nonlinear primary path (NPP) and nonlinear secondary path (NSP) conditions.
In this paper, we analyze the two-node joint clock synchronization and ranging problem. We focus on the case of nodes that employ time-to-digital converters to determine the range between them precisely. This specific design choice leads to a sawtooth model for the captured signal, which has not been studied before from an estimation theoretic standpoint.
This paper formulates a multitask optimization problem where agents in the network have individual objectives to meet, or individual parameter vectors to estimate, subject to a smoothness condition over the graph. The smoothness condition softens the transition in the tasks among adjacent nodes and allows incorporating information about the graph structure into the solution of the inference problem.
Users of X-ray (micro-)CT in research environments often study many different types of objects, with many different research questions. For each new scan, the settings of the scan (number of angles, dose, cone angle) are chosen by the user, often based on how much time is available, the dose sensitivity of the sample, and geometrical characteristics of the particular CT-scanner that is used.
The coded aperture snapshot spectral imager (CASSI) is a computational imaging system that acquires a three dimensional (3D) spectral data cube by a single or a few two dimensional (2D) measurements. The 3D data cube is reconstructed computationally. Binary on-off random coded apertures with square pixels are primarily implemented in CASSI systems to modulate the spectral images in the image plane.
The problem of blind audio source separation (BASS) in noisy and reverberant conditions is addressed by a novel approach, termed Global and LOcal Simplex Separation (GLOSS), which integrates full- and narrow-band simplex representations. We show that the eigenvectors of the correlation matrix between time frames in a certain frequency band form a simplex that organizes the frames according to the speaker activities in the corresponding band.
This article investigates deep learning based single- and multi-channel speech dereverberation. For single-channel processing, we extend magnitude-domain masking and mapping based dereverberation to complex-domain mapping, where deep neural networks (DNNs) are trained to predict the real and imaginary (RI) components of the direct-path signal from reverberant (and noisy) ones.
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The IEEE Signal Processing Society is dedicated to supporting the professional growth and career advancement of its members in the dynamic field of signal processing. Learn More
Signal processing education and professional development program for all career levels. Learn more.