Results 21 to 30 of about 2,236 (212)
Beamforming with sparse prior in ultrasound medical imaging [PDF]
2014 IEEE International Ultrasonics Symposium, 2014 Nowadays the classical Delay-and-Sum (DAS) beamformer is extensively used in ultrasound imaging due to its low computational characteristics. However, it suffers from high sidelobe level, poor resolution and low contrast. An alternative is the Minimum-Variance (MV) beamformer which results in a higher image quality both in terms of spatial resolution ...
Szasz, Teodora +3 more
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Frequency divided group beamforming with sparse spacefrequency code for above 6 GHz URLLC systems
ETRI Journal, 2022 In this study, we propose a limited feedback-based frequency divided group beamforming with sparse space-frequency transmit diversity coded orthogonal frequency division multiplexing (OFDM) system for ultrareliable low latency communication (URLLC ...
Chanho Yoon +3 more
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Kronecker-Product Beamforming With Sparse Concentric Circular Arrays
IEEE Open Journal of Signal Processing, 2023 This article presents a Kronecker-product (KP) beamforming approach incorporating sparse concentric circular arrays (SCCAs). The locations of the microphones on the SCCA are optimized concerning the broadband array directivity over a wide range of ...
Gal Itzhak, Israel Cohen
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On the Sparse Beamformer Design [PDF]
Sensors, 2018 In designing acoustic broadband beamformers, the complexity can grow significantly when the number of microphones and the filter length increase. It is advantageous if many of the filter coefficients are zeroes so that the implementation can be executed with less computation.
Mingjie Gao +2 more
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Sparse Convolutional Beamforming for Ultrasound Imaging [PDF]
IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control, 2018 The standard technique used by commercial medical ultrasound systems to form B-mode images is delay and sum (DAS) beamforming. However, DAS often results in limited image resolution and contrast, which are governed by the center frequency and the aperture size of the ultrasound transducer.
Regev Cohen, Yonina C. Eldar
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Analog Beamforming with Antenna Selection for Large-Scale Antenna Arrays [PDF]
, 2021 peer reviewedIn large-scale antenna array (LSAA) wireless communication systems employing analog beamforming architectures, the placement or selection of a subset of antennas can significantly reduce the power consumption and hardware complexity. In this
OTTERSTEN, Björn +9 more
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Beamformers for sparse recovery
2013 IEEE International Conference on Acoustics, Speech and Signal Processing, 2013 In sparse recovery from measurement data a common approach is to use greedy pursuit reconstruction algorithms. Most of these algorithms have a correlation filter for detecting active components in the sparse data. In this paper, we show how modifications can be made for the greedy pursuit algorithms so that they use beamformers instead of the standard ...
Martin Sundin +2 more
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Sparse Array Beamformer Design via ADMM
2022 IEEE 12th Sensor Array and Multichannel Signal Processing Workshop (SAM), 2022 In this paper, we devise a sparse array design algorithm for adaptive beamforming. Our strategy is based on finding a sparse beamformer weight to maximize the output signal-to-interference-plus-noise ratio (SINR). The proposed method utilizes the alternating direction method of multipliers (ADMM), and admits closed-form solutions at each ADMM iteration.
Huiping Huang +2 more
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New Directions In Sparse Sampling and Estimation For Underdetermined Systems [PDF]
, 2013 A central objective in signal processing is to infer meaningful information from a set of measurements or data. While most signal models have an overdetermined structure (the number of unknowns less than the number of equations), traditionally very few ...
Piya Pal, Pal, Piya
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Fully complex-valued radial basis function networks: orthogonal least squares regression and classification [PDF]
, 2008 We consider a fully complex-valued radial basis function (RBF) network for regression and classification applications. For regression problems, the locally regularised orthogonal least squares (LROLS) algorithm aided with the D-optimality experimental ...
Harris, C. J. +7 more
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