Showing papers in "Digital Signal Processing in 2019"

TL;DR: In this paper, the authors explain how the first chapter of the massive MIMO research saga has come to an end, while the story has just begun, and outline five new massive antenna array related research directions.

TL;DR: An overview of the emerging field of massive MIMO localization is provided, which can be used to meet the requirements of 5G, by exploiting different spatial signatures of users.

TL;DR: A novel radar-based human motion recognition technique that exploits the temporal sequentiality of human motions by employing a stacked recurrent neural network with long short-term memory units to extract sequential features for automatic motion classification.

TL;DR: A computationally efficient parallel factor (PARAFAC) estimator is proposed, which is suitable for direction-of-arrival (DOA) estimation in colocated MIMO radar with large antenna arrays as well as nonorthogonal waveforms and the stochastic Cramer-Rao bound on DOA estimation with waveform imperfectly is derived.

TL;DR: A novel localization method for mixed near-field and far-field rectilinear sources is proposed using the noncircular information for a symmetric uniform linear array (ULA) and yields a performance better than existing ones.

TL;DR: A new TFA method, named synchroextracting chirplet transform (SECT), is proposed, which sharpens the TF representation by extracting the TF points satisfying IF equation, and retains an excellent signal reconstruction ability.

TL;DR: A straightforward data-based method of determining the optimal number of bins in a uniform bin-width histogram is introduced by assigning a multinomial likelihood and a non-informative prior to derive the posterior probability for the number of Bin heights in a piecewise-constant density model given the data.

TL;DR: An application-layer scheme to jointly exploit the available bandwidth from the LTE and Wi-Fi networks in 360-degree video streaming and a novel buffer strategy is proposed to mitigate the influence of short-time prediction problem for transmitting360-degree videos in time-varying networks.

TL;DR: The performance improvement of the proposed DU-CNOMA over the conventional CRS using NOMA is proved through analysis and computer simulation, and the correctness of the author's analysis is provedthrough a strong agreement between simulation and analytical results.

TL;DR: A ( k, n ) threshold partial reversible absolute moment block truncation coding (AMBTC) based SIS scheme with steganography and authentication with effectiveness and advantages is proposed.

TL;DR: In this paper, the authors investigated a quasi-synchronous VLP system, in which the LED transmitters are synchronous among themselves but are not synchronized with the receiver.

TL;DR: The free energy principle inspired visual quality assessment metrics with a comparison in terms of algorithm design and performance are reviewed.

TL;DR: The proposed front-end acoustic features are observed to be more robust towards ambient noise and pitch variations than the conventional MFCC features as demonstrated by the experimental evaluations presented in this study.

TL;DR: In this article, an ensemble of deep neural networks (DNNs) and an ensembles of jointly trained DNNs are used to cope with a wide range of reverberations in real-world situations.

TL;DR: A novel blind quality assessment method for SCIs via the CNN is developed that takes the entire image as inputs and is comparable to reference-based SCI quality assessment metrics and is superior to the state-of-the-art NSIquality assessment metrics.

TL;DR: The weighted GD (WGD) and the generalized likelihood ratio test for GD (GLRT-GD) are proposed to be used for coarse spectrum sensing when the noise power is known and unknown, respectively.

TL;DR: Each decomposition strategy is better devoted to particular scenarios, however, without any previous knowledge on data, GHKSS confirmed to work as a fair and general baseline besides its time complexity.

TL;DR: Two sparsity-aware normalized subband adaptive filter algorithms are proposed by using the gradient descent method to minimize a combination of the original NSAF cost function and the l 1 -norm penalty function on the filter coefficients, thus improving the performance when identifying sparse systems.

TL;DR: In this article, low frequency frame-wise normalization (LFFN) is proposed as one of the modules in feature extraction process that is hypothesized to help in capturing the artifacts from the playback speech.

TL;DR: Inspired by the idea of bounded non-linear covariance (BNC), a novel subspace based method for DOA estimation is proposed, named NC-BNC-ESPRIT, which uses the BNC matrix to create a signal subspace of extended array outputs and it can handle theDOA estimation for noncircular (NC) signals in presence of impulsive noise.

TL;DR: A Joint Low-Complexity Regularized ZF (JLRZF) equalizer to perform both equalization and Carrier Frequency Offset (CFO) compensation, jointly, in Underwater Acoustic (UWA)-OFDM systems is presented.

TL;DR: A new perspective is given on a key relation associated with spreads in time, frequency, time-frequency and linear canonical transform (LCT) domains, from which a new LCT uncertainty principle for complex signals using the ASM's rotation orthogonal decomposition is derived.

TL;DR: A new sparse time–frequency representation model is put forward by using the Lp-quasinorm constraint, which is capable of fitting the sparsity prior knowledge in the frequency domain, and the alternating direction method of multipliers (ADMM) is adopted to solve the model.

TL;DR: A two-stage estimating signal parameters via rotation invariance technique (ESPRIT) algorithm for FDA-MIMO radar to estimate both range and angle of targets, along with the proposed pairing method for unambiguous estimates are proposed.

TL;DR: In DLSL, a new subspace learning algorithm (SL) is proposed by using sparse constraint, low-rank technology and the authors' label relaxation model to reduce the disparity between domains to achieve better performance than other state-of-the-art algorithms.

TL;DR: The proposed approach is compared to other dynamic texture methods on two very well known dynamic texture database and on traffic condition classification, and outperform in most of the cases.

TL;DR: By implementing IDFT on the second-order virtual array signals characterized by the equivalent spatial frequency, it is proved that the resulting spatial response enables to effectively estimate both DOA and source power with an increased number of DOFs.

TL;DR: The concept of distortion sensitivity as a property of the reference image that compensates for a given computational quality model a potential lack of perceptual relevance is derived and applied to the PSNR and leads to a local weighting scheme for the MSE.

TL;DR: This paper designs the Rao and generalized likelihood ratio test (GLRT) detectors by the two-step procedure, which incorporates persymmetric structure of received data and ensures constant false alarm rate property.

TL;DR: A robust region-based active contour model driven by fuzzy c-means energy that draws upon the clustering intensity information for fast image segmentation that has a good robustness on initial contour, parameters and different kinds of noise.