IEEE Signal Processing Letters | All Volumes | IEEE Xplore

Issue 4 • April-2015

Front Cover

Publication Year: 2015,Page(s):C1 - C1

Front Cover

Year: 2015 | Volume: 22 | Issue: 4

IEEE Signal Processing Letters publication information

Publication Year: 2015,Page(s):C2 - C2

IEEE Signal Processing Letters publication information

Year: 2015 | Volume: 22 | Issue: 4

Table of Contents

Publication Year: 2015,Page(s):381 - 382

Table of Contents

Year: 2015 | Volume: 22 | Issue: 4

Table of Contents

Publication Year: 2015,Page(s):383 - 384

Table of Contents

Year: 2015 | Volume: 22 | Issue: 4
The traditional schemes for the synchronization in the OFDM transmission, such as the Schmidl&Cox, Minn and Park algorithms, utilize the only every second or fourth subcarriers of the preamble symbol. This regular subcarrier occupation pattern does not meet the requirement of Non-Continuous OFDM (NC-OFDM) with the arbitrary spectrum holes free from the interference with the primary users. In this ...Show More
Fingerprint image enhancement is one of the most crucial steps in an automated fingerprint identification system. In this paper, an effective algorithm for fingerprint image quality improvement is proposed. The algorithm consists of two stages. The first stage is decomposing the input fingerprint image into four subbands by applying two-dimensional discrete wavelet transform. At the second stage, ...Show More
Different local manifold learning methods are developed based on different geometric intuitions and each method only learns partial information of the true geometric structure of the underlying manifold. In this letter, we introduce a novel method to fuse the geometric information learned from local manifold learning algorithms to discover the underlying manifold structure more faithfully. We firs...Show More
In this letter, we propose a semiblind channel estimation technique for OFDM/OQAM wireless systems. The proposed technique exploits the real property of transmitted symbols to blindly identify the channel-induced rotation in the received signal, thereby reducing the pilot overhead for estimation purpose. Specifically, the channel phase over each subcarrier can be obtained from the spatial-sign cov...Show More
In this letter, we design iterative receiver algorithms for joint frequency-domain equalization and decoding in a single carrier system assuming perfect channel state information. Based on an approximate inference framework that combines belief propagation (BP) and the mean field (MF) approximation, we propose two receiver algorithms with, respectively, parallel and sequential message-passing sche...Show More

A Near-ML MIMO Subspace Detection Algorithm

Mohammad M. Mansour

Publication Year: 2015,Page(s):408 - 412
Cited by: Papers (25)
A low-complexity MIMO detection scheme is presented that decomposes a MIMO channel into multiple decoupled subsets of streams that can be detected separately. The scheme employs QL decomposition followed by elementary matrix operations to transform the channel matrix into a generalized elementary structure matching the subsets of streams to be detected. The proposed scheme avoids matrix inversion ...Show More
Hostile jamming can cause significant performance degradation in wireless communications, but it also provides an unexplored source of additional signal power. In this letter, we propose an energy-harvesting receiver for two-way orthogonal frequency division multiplexing (OFDM) systems under hostile jamming. More specifically, in the downlink, the receiver is designed to simultaneously process inf...Show More
In this work we develop a post-processing algorithm which enhances the results of the existing image deblurring methods. It performs additional edge sharpening using grid warping. The idea of the proposed algorithm is to transform the neighborhood of the edge so that the neighboring pixels move closer to the edge, and then resample the image from the warped grid to the original uniform grid. The p...Show More
An estimation setting is considered, where a number of sensors transmit their observations of a physical phenomenon, described by one or more random variables, to a sink over noisy communication channels. The goal is to minimize a quadratic distortion measure (Minimum Mean Square Error - MMSE) under a global power constraint on the sensors' transmissions. Linear MMSE encoders and decoders, paramet...Show More
This letter proposes a new feature describing the trajectories of surface patches (ToSP) on human bodies for action recognition by a novel scheme of utilizing RGB and depth videos. RGB data contains appearance information by which we track specific patches on body surfaces while depth data contains spatial information by which we describe surface patches. Specifically, we use spatial-temporal inte...Show More
In this letter, we propose a multi-task compressive sensing algorithm for the reconstruction of clustered sparse entries based on hierarchical Bayesian framework. By extending a paired spike-and-slab prior to a general multi-task model, the proposed algorithm has the capability of modeling both inter-task and intra-task dependencies of the observation data. The latter is achieved by imposing a clu...Show More
From the co-array perspective, sparse spatial sampling can significantly increase the degrees-of-freedom (DOFs), enabling us to perform underdetermined direction-of-arrival (DOA) estimation. By leveraging the increased DOFs from the sparse spatial sampling, we develop a new underdetermined DOA estimation method for wideband signals, named wideband sparse spectrum fitting (W-SpSF) estimator. In W-S...Show More
Motivated by application of Gaussian sum filters (GSF) and multiple model adaptive estimation (MMAE) approaches in scenarios where assumption of proper (circular) Gaussian signals is not valid, the letter proposes a novel complex-valued Gaussian sum filter (C/GSF) for non-linear filtering of non-Gaussian/non-circular measurement noise. Although the literature on recursive state estimation using GS...Show More
This letter proposes an accurate human pose estimation method that uses a modified kernel density approximation (m-KDA) to multiple pose hypotheses. Existing methods show poor human pose estimation because of cluttered background or self-occlusion by the human. To improve the pose estimation accuracy, we propose to use m-KDA to aggregate multiple pose estimation results. First, we use the flexible...Show More
This letter presents a speech enhancement technique combining statistical models and non-negative matrix factorization (NMF) with on-line update of speech and noise bases. The statistical model-based enhancement methods have been known to be less effective to non-stationary noises while the template-based enhancement techniques can deal with them quite well. However, the template-based enhancement...Show More
The task of re-identifying a person that moves across cameras fields-of-view is a challenge to the community known as the person re-identification problem. State-of-the art approaches are either based on direct modeling and matching of the human appearance or on machine learning-based techniques. In this work we introduce a novel approach that studies densely localized image dissimilarities in a l...Show More
The Wigner distribution (WD) and ambiguity function (AF) associated with the linear canonical transform (LCT) play a major role in non-stationary signal processing. Many novel time-frequency analysis tools for it exist, such as the linear canonical WD (LCWD), the linear canonical AF (LCAF), the WD in the LCT domain (WDL) and the AF in the LCT domain (AFL). The purpose of this letter is to introduc...Show More
A new in-loop filter, sample adaptive offset (SAO) allows the latest video compression standard, HEVC or H.265, to achieve higher coding efficiency both in objective and subjective measures. However, it requires additional operations to estimate the best SAO parameters per coding tree unit (CTU) during the video encoding process, which often leads to many practical issues such as high computationa...Show More
In this work, we propose a strategy for optimizing a superpixel algorithm for video signals, in order to get closer to real time performances which are on the one hand needed for egocentric vision applications and on the other must be bearable by wearable technologies. Instead of applying the algorithm frame by frame, we propose a technique inspired to Bayesian filtering and to video coding which ...Show More
An unscented Kalman filter-based constant modulus adaptation algorithm (UKF-CMA) is proposed for blind uniform linear beamforming. The proposed algorithm is obtained by first developing a model of the constant modulus (CM) criterion and then fitting that model into the Kalman filter-style state space model by using an auxiliary parameter. The proposed algorithm does not require a priori informatio...Show More
Minimum variance distortionless response (MVDR) is a classic design criteria in signal adaptive spectral analysis as well as filter design. We extend this approach to filterbanks with the constraint that transform domain signal components must be uncorrelated. Our analysis shows that filterbanks based on Vandermonde decomposition of the autocorrelation matrix correspond to the non-uniform discrete...Show More

Contact Information

Editor-in-Chief
Christ D. Richmond
Duke University
Durham
USA
christ.richmond@duke.edu