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1043 results found.
Section: Publications & Resources
Publication: IEEE Signal Processing Magazine
This article examines the problem of interference in automotive radar. Different types of automotive radar as well as mechanisms and characteristics of interference and the effects of interference on radar system performance are described. The interference-to-noise ratio (INR) at the output of a detector is a measure of the susceptibility of a radar to interference. The INR is derived from different types of interfering and victim radars and depends on the location of both as well as parameters such as transmit power, antenna gain, and bandwidth.
Section: Publications & Resources
Publication: IEEE Signal Processing Magazine
Today, many devices (e.g., cars and other vehicles) we operate for various tasks (e.g., to go from place A to place B) are changing: in the past, they were characterized by a body and control actuators that allowed us to perform these tasks. These days, they are not simply passive recipients of our instructions;
Section: Publications & Resources
Publication: IEEE Transactions on Signal Processing
Nonlinear static multiple-input multiple-output (MIMO) systems are analyzed. The matrix formulation of Bussgang's theorem for complex Gaussian signals is rederived and put in the context of the multivariate cumulant series expansion. The attenuation matrix is a function of the input signals’ covariance and the covariance of the input and output signals.
Section: Publications & Resources
Publication: IEEE Transactions on Signal Processing
Substantial progress has been made recently on developing provably accurate and efficient algorithms for low-rank matrix factorization via nonconvex optimization. While conventional wisdom often takes a dim view of nonconvex optimization algorithms due to their susceptibility to spurious local minima, simple iterative methods such as gradient descent have been remarkably successful in practice.
Section: Publications & Resources
Publication: IEEE Transactions on Signal Processing
We address a robust detection problem for MIMO radars in Gaussian noise with unknown covariance matrix, for the mismatched case where the nominal transmit (or receive) steering vector may not be aligned with the true transmit (or receive) steering vector. Subspace models are adopted for taking into account these mismatches.
Section: Publications & Resources
Publication: IEEE Transactions on Signal Processing
Structural equation models (SEMs) and vector autoregressive models (VARMs) are two broad families of approaches that have been shown useful in effective brain connectivity studies. While VARMs postulate that a given region of interest in the brain is directionally connected to another one by virtue of time-lagged influences, SEMs assert that directed dependencies arise due to instantaneous effects...
Section: Publications & Resources
Publication: IEEE Signal Processing Letters
Many well-known line spectral estimators may experience significant performance loss with noisy measurements. To address the problem, we propose a deep learning denoising based approach for line spectral estimation. The proposed approach utilizes a residual learning assisted denoising convolutional neural network (DnCNN) trained to recover the unstructured noise component, which is used to denoise the original measurements.
Section: Publications & Resources
Publication: IEEE Signal Processing Letters
Two-directional two-dimensional canonical correlation analysis ((2D) 2 CCA) directly seeks linear relationship between different image data sets without reshaping images into vectors. However, it fails in finding the nonlinear correlation.
Section: Publications & Resources
Publication: IEEE Signal Processing Letters
The multiple signal classification (MUSIC) algorithmis computationally expensive in the application to joint two-dimensional (2-D) direction-of-arrival (DOA) and time-of-arrival (TOA) estimation based on uniform circular array (UCA) using orthogonal frequency-division multiplexing (OFDM) signal. This letter proposed an efficient way to compute the 3-D spatial-temporal spectrum.
Section: Publications & Resources
A sound field reproduction method based on the spherical wavefunction expansion of sound fields is proposed, which can be flexibly applied to various array geometries and directivities. First, we formulate sound field synthesis as a minimization problem of some norm on the difference between the desired and synthesized sound fields, and then the optimal driving signals are derived by using the spherical wavefunction expansion of the sound fields.
