# IEEE Transactions on Signal Processing

### Early Access Articles

Early Access articles are made available in advance of the final electronic or print versions. Early Access articles are peer reviewed but may not be fully edited. They are fully citable from the moment they appear in IEEE Xplore.

## Filter Results

Displaying Results 1 - 24 of 24
• ### Optimal Mean-Reverting Portfolio With Leverage Constraint for Statistical Arbitrage in Finance

Publication Year: 2019, Page(s): 1
| | PDF (6385 KB)

The optimal mean-reverting portfolio (MRP) design problem is an important task for statistical arbitrage, a.k.a. pairs trading, in the financial markets. The target of the problem is to construct a portfolio of the underlying assets (possibly with an asset selection target) that can exhibit a satisfactory mean reversion property and a desirable variance property. In this paper, the optimal MRP des... View full abstract»

• ### Sparse Channel Estimation for OFDM-Based Underwater Acoustic Systems in Rician Fading with a New OMP-MAP Algorithm

Publication Year: 2019, Page(s): 1
| | PDF (9005 KB)

In this paper, a new channel estimation algorithm is proposed that exploits channel sparsity in the time domain for an orthogonal frequency division multiplexing (OFDM)-based underwater acoustical communications systems in the presence of Rician fading. A path-based channel model is used, in which the channel is described by a limited number of paths, each characterized by a delay, Doppler scale, ... View full abstract»

• ### Robust Distributed Diffusion Recursive Least Squares Algorithms with Side Information for Adaptive Networks

Publication Year: 2019, Page(s): 1
| | PDF (3209 KB)

This work develops robust diffusion recursive least squares algorithms to mitigate the performance degradation often experienced in networks of agents in the presence of impulsive noise. The first algorithm minimizes an exponentially weighted least-squares cost function subject to a time-dependent constraint on the squared norm of the intermediate update at each node. A recursive strategy for comp... View full abstract»

• ### Optimal Channel Estimation for Reciprocity-Based Backscattering with a Full-Duplex MIMO Reader

Publication Year: 2019, Page(s): 1
| | PDF (2983 KB)

Backscatter communication (BSC) technology can enable ubiquitous deployment of low-cost sustainable wireless devices. In this work we investigate the efficacy of a full-duplex multiple-input-multiple-output (MIMO) reader for enhancing the limited communication range of monostatic BSC systems. As this performance is strongly influenced by the channel estimation (CE) quality, we first derive a novel... View full abstract»

• ### Detecting Approximate Reflection Symmetry in a Point Set using Optimization on Manifold

Publication Year: 2019, Page(s): 1
| | PDF (21162 KB) |  Media

We propose an algorithm to detect approximate reflection symmetry present in a set of volumetrically distributed points belonging to $\mathbb{R}^d$ containing a distorted reflection symmetry pattern. We pose the problem of detecting approximate reflection symmetry as the problem of establishing correspondences between the points which are reflections of each other and... View full abstract»

• ### Mismatched Signal Rejection Performance of the Persymmetric GLRT Detector

Publication Year: 2019, Page(s): 1
| | PDF (212 KB)

We analytically evaluate the mismatched signal rejection performance of a persymmetric generalized likelihood ratio test (PGLRT) detector in a mismatched case where the nominal target steering vector is not aligned with the true one. This PGLRT detector can be applied to target detection in Gaussian noise with unknown covariance matrix for several cases where the data under test are collected from... View full abstract»

• ### Marginalized Particle Filtering and Related Filtering Techniques as Message Passing

Publication Year: 2019, Page(s): 1
| | PDF (1235 KB)

In this manuscript a factor graph approach is employed to investigate the recursive filtering problem for conditionally linear Gaussian state-space models. First, we derive a new factor graph for the considered filtering problem; then, we show that applying the sum-product rule to our graphical model results in both known and novel filtering techniques. In particular, we prove that: a) marginalize... View full abstract»

• ### Event-Driven Sensor Scheduling for Mission-Critical Control Applications

Publication Year: 2019, Page(s): 1
| | PDF (2525 KB)

In this paper, we consider a mission-critical control system, where an unstable dynamic plant is monitored by a number of distributed sensors connected to the controller over the wireless fading channels. We focus on the dynamic sensor scheduling to stabilize the unstable dynamic plant. The dynamic sensor scheduling is modeled as a non-convex drift-plus-penalty minimization problem. To improve sch... View full abstract»

• ### Two-Channel Critically-Sampled Graph Filter Banks With Spectral Domain Sampling

Publication Year: 2019, Page(s): 1
| | PDF (2939 KB)

We propose two-channel critically-sampled filter banks for signals on undirected graphs that utilize spectral domain sampling. Unlike conventional approaches based on vertex domain sampling, our transforms have the following desirable properties: 1) perfect reconstruction regardless of the characteristics of the underlying graphs and graph variation operators and 2) a symmetric structure; i.e., bo... View full abstract»

• ### SINR Distribution for the Persymmetric SMI Beamformer With Steering Vector Mismatches

Publication Year: 2019, Page(s): 1
| | PDF (190 KB)

We examine the normalized output signal-to-interference-plus-noise ratio (SINR) of a sample matrix inversion beamformer exploiting the persymmetry of the received data. The persymmetry commonly exists in the received data, when a symmetrically spaced linear array and/or symmetrically spaced pulse trains are utilized. An exact expression for the probability density function (PDF) of the normalized ... View full abstract»

• ### Robust Beamforming Design for MISO Bursty Interference Channels under Traffic Uncertainties

Publication Year: 2019, Page(s): 1
| | PDF (736 KB)

In this study, we consider a coordinated beamforming design for a multiple-input single-output (MISO) bursty interference channel. In practical scenarios, the distributed medium access control mechanisms or the decentralized networking protocols across different users contribute to the bursty nature of network traffic. The potential gains provided by such burstiness can be exploited by feeding bac... View full abstract»

• ### Anomaly Detection in Partially Observed Traffic Networks

Publication Year: 2019, Page(s): 1
| | PDF (3302 KB)

This paper addresses the problem of detecting anomalous activity in traffic networks where the network is not directly observed. Given knowledge of what the node-to-node traffic in a network should be, any activity that differs significantly from this baseline would be considered anomalous. We propose a Bayesian hierarchical model for estimating the traffic rates and detecting anomalous changes in... View full abstract»

• ### Further Results on the Cramar-Rao Bound for Sparse Linear Arrays

Publication Year: 2019, Page(s): 1
| | PDF (1275 KB)

With uniform linear arrays (ULAs), subspace-based direction of arrival (DOA) estimation algorithms, such as MUtiple SIgnal Classification (MUSIC), can only resolve M - 1 sources using M sensors. Sparse linear arrays, such as co-prime and nested arrays, can identify up O(M$^2$) uncorrelated sources using only O(M) sensors when such DOA estimation algorithms are applied... View full abstract»

• ### Quaternion-Based Multiscale Analysis for Feature Extraction of Hyperspectral Images

Publication Year: 2019, Page(s): 1
| | PDF (1599 KB)

This paper proposes a new method called multiscale quaternion Weber local descriptor histogram (MQWLDH) for feature extraction of hyperspectral images (HSIs), which is used to model spatial information based on the corresponding spectral features. The proposed method first transforms spectral data into an orthogonal space using principal component analysis, and extracts the first three principal c... View full abstract»

• ### A Robust Spectral Estimator with Application to a Noise Corrupted Process

Publication Year: 2019, Page(s): 1
| | PDF (2351 KB) |  Media

When a data set is corrupted by noise, the model for the data generating process is misspecified and can cause parameter estimation problems. As an example, in the case of a Gaussian autoregressive (AR) process corrupted by noise, the data is more accurately modeled as an autoregressive moving average (ARMA) process rather than an AR process. This misspecification leads to bias, and hence, low res... View full abstract»

• ### Recursive Maximum Likelihood Algorithm for Dependent Observations

Publication Year: 2019, Page(s): 1
| | PDF (3918 KB)

A recursive maximum-likelihood algorithm (RML) is proposed that can be used when both the observations and the hidden data have continuous values and are statistically dependent between different time samples. The algorithm recursively approximates the probability density functions of the observed and hidden data by analytically computing the integrals with respect to the state variables, where th... View full abstract»

• ### Rational Optimization for Nonlinear Reconstruction with Approximate${\ell}_{0}$Penalization

Publication Year: 2018, Page(s): 1
| | PDF (324 KB)

Recovering nonlinearly degraded signal in the presence of noise is a challenging problem. In this work, this problem is tackled by minimizing the sum of a non convex least-squares fit criterion and a penalty term. We assume that the nonlinearity of the model can be accounted for by a rational function. In addition, we suppose that the signal to be sought is sparse and a rational approximation of t... View full abstract»

• ### Sampling and Super-resolution of Sparse Signals Beyond the Fourier Domain

Publication Year: 2018, Page(s): 1
| | PDF (3951 KB)

Recovering a sparse signal from its low-pass projections in the Fourier domain is a problem of broad interest in science and engineering and is commonly referred to as super- resolution. In many cases, however, Fourier domain may not be the natural choice. For example, in holography, low-pass projections of sparse signals are obtained in the Fresnel domain. Similarly, time-varying system identific... View full abstract»

• ### Parameter Estimation Based on Scale-Dependent Algebraic Expressions and Scale-Space Fitting

Publication Year: 2018, Page(s): 1
| | PDF (10172 KB) |  Media

We present our results of applying wavelet theory to the classic problem of estimating the unknown parameters of a model function subject to noise. The model function studied in this context is a generalization of the second order Gaussian derivative of which the Gaussian function is a special case. For all five model parameters (amplitude, width, location, baseline, undershoot-size), scale-depend... View full abstract»

• ### Multi-Snapshot Spectrum Sensing for Cognitive Radar via Block-Sparsity Exploitation

Publication Year: 2018, Page(s): 1
| | PDF (6496 KB)

Two-dimensional (2-D) spectrum sensing is addressed in the context of a cognitive radar to gather real-time space-frequency electromagnetic awareness. Assuming a sensor equipped with multiple receive antennas, a discrete-time sensing signal model formally accounting for multiple snapshots of observations is introduced. Hence, a new signal processing strategy exploiting the inherent block-sparsity ... View full abstract»

• ### Transmitter Precoder Design to Improve the Performance of the MUSIC Algorithm

Publication Year: 2018, Page(s): 1
Cited by:  Papers (5)
| | PDF (662 KB)

Using the MUSIC (MUltiple SIgnal Classification) algorithm to estimate the angle-of-arrival (AoA), we derive a new asymptotic error variance bound when the transmitted signal can be pre-processed. We next propose a precoder design to achieve this bound. However, such an optimal precoder requires channel state information at the transmitter (CSIT) exclusive of the receiver array which cannot be sep... View full abstract»

• ### Underdetermined DOA Estimation for Wide-Band Stationary Sources in Unknown Noise Environment

Publication Year: 2018, Page(s): 1
Cited by:  Papers (1)
| | PDF (353 KB)

Underdetermined direction-of-arrival estimation for wide-band stationary signals is addressed in this correspondence. By properly employing the diversities in frequency domain, the proposed method is able to significantly increase the degrees of freedom of a uniform linear array, which enables us to handle more sources than sensors. Meanwhile, as the unknown noise can be efficiently suppressed in ... View full abstract»

• ### Dynamic Spectrum Management in DSL With Asynchronous Crosstalk

Publication Year: 2018, Page(s): 1
Cited by:  Papers (1)
| | PDF (413 KB)

In this paper we focus on discrete multitone (DMT) dynamic spectrum management (DSM) in digital subscriber lines (DSL) networks with asynchronous crosstalk. DSM aims to optimally allocate per-user transmit spectra so that the effect of multi-user crosstalk is minimized and the capabilities of the network maximized. Most DSM solutions so far address an idealized situation, one in which all users DM... View full abstract»

• ### Novel class of digital integrators and differentiators

Publication Year: 2018, Page(s): 1
Cited by:  Papers (5)
| | PDF (340 KB)

A novel class of IIR (infinite impulse response) digital integrators and differentiators is developed. A class of digital integrators is first derived from a class of numerical integration rules. A class of digital differentiators is subsequently obtained by inverting the transfer functions of the obtained integrators and stabilizing the resulting transfer functions together with magnitude compens... View full abstract»

## Aims & Scope

IEEE Transactions on Signal Processing covers novel theory, algorithms, performance analyses and applications of techniques for the processing, understanding, learning, retrieval, mining, and extraction of information from signals

Full Aims & Scope

## Meet Our Editors

Editor-in-Chief
Pier Luigi Dragotti
EEE Department
Imperial College London