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Section: Publications & Resources
Publication: IEEE Transactions on Signal Processing
Linear data-detection algorithms that build on zero forcing (ZF) or linear minimum mean-square error (L-MMSE) equalization achieve near-optimal spectral efficiency in massive multi-user multiple-input multiple-output (MU-MIMO) systems.
Section: Publications & Resources
Publication: IEEE Transactions on Signal Processing
In this paper, we study blind channel-and-signal estimation by exploiting the burst-sparse structure of angular-domain propagation channels in massive MIMO systems. The state-of-the-art approach utilizes the structured channel sparsity by sampling the angular-domain channel representation with a uniform angle-sampling grid, a.k.a. virtual channel representation.
Section: Publications & Resources
Publication: IEEE Transactions on Signal Processing
This paper considers and analyzes the performance of semiblind, training, and data-aided channel estimation schemes for multiple-input multiple-output (MIMO) filter bank multicarrier (FBMC) systems with offset quadrature amplitude modulation.
Section: Publications & Resources
Publication: IEEE Transactions on Signal Processing
The topic of sequence design has received considerable attention due to its wide applications in active sensing. One important desired property for the design sequence is the spectral shape. In this paper, the sequence design problem is formulated by minimizing the regularized spectral level ratio subject to a peak-to-average power ratio constraint.
Section: Publications & Resources
Publication: IEEE Transactions on Signal Processing
The problem of detecting a high-dimensional signal based on compressive measurements in the presence of an eavesdropper (Eve) is studied in this paper. We assume that a large number of sensors collaborate to detect the presence of sparse signals while the Eve has access to all the information transmitted by the sensors to the fusion center (FC).
Section: Events
Lecture Date: March 12-13, 2020
Chapter: Pune
Chapter Chair: Anil S. Tavildar
Topic: Array processing and beamforming with Kronecker products,
Audio-Visual Voice Activity Detection Using Deep Neural Networks
Section: Events
Lecture Date: March 16-17, 2020
Chapter: Bangalore
Chapter Chair: Venkatesh Radhakrishnan
Topic: Optimal Multichannel signal enhancement, Audio-Visual
Voice Activity Detection Using Deep Neural Networks
Section: Events
Lecture Date: March 19-21, 2020
Chapter: Chennai
Chapter Chair: S. Salivahanan
Topic: Audio-Visual Voice Activity Detection Using Deep Neural Networks,
Array processing and beamforming with Kronecker products
Section: Publications & Resources
Anna Scaglione (F) (M.Sc.'95, Ph.D. '99) is currently a professor in electrical and computer engineering at Arizona State University (ASU). She was Professor of Electrical Engineering previously at the University of California at Davis (2008-2014), and at Cornell University, (2001-2008).
Summary:
Biamp Systems is seeking an intelligent and motivated DSP Engineer that is passionate about digital audio theory and algorithm implementation. In this role, the DSP Engineer designs, develops, maintains, and tests DSP audio algorithms and applications used to provide novel solutions in teleconferencing, video conferencing, and sound reinforcement systems. The DSP Engineer may also contribute to audio centric machine learning projects, designing and creating data sets and managing machine learning infrastructure systems.
