# 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 - 25 of 42
• ### A Binning Approach to Quickest Change Detection with Unknown Post-Change Distribution

Publication Year: 2018, Page(s): 1
| | PDF (2249 KB)

The problem of quickest detection of a change in distribution is considered under the assumption that the pre-change distribution is known, and the post-change distribution is only known to belong to a family of distributions distinguishable from a discretized version of the pre-change distribution. A sequential change detection procedure is proposed that partitions the sample space into a finite ... View full abstract»

• ### SUPERVISED LEARNING UNDER DISTRIBUTED FEATURES

Publication Year: 2018, Page(s): 1
| | PDF (2198 KB)

This work studies the problem of learning under both large datasets and large-dimensional feature space scenarios. The feature information is assumed to be spread across agents in a network, where each agent observes some of the features. Through local cooperation, the agents are supposed to interact with each other to solve an inference problem and converge towards the global minimizer of an empi... View full abstract»

• ### Graph-Variate Signal Analysis

Publication Year: 2018, Page(s): 1
| | PDF (1531 KB)

Incorporating graphs in the analysis of multivariate signals is becoming a standard way to understand the interdependency of activity recorded at different sites. The new research frontier in this direction includes the important problem of how to assess dynamic changes of signal activity. We address this problem in a novel way by defining the graph-variate signal alongside methods for its analysi... View full abstract»

• ### Sparse Antenna and Pulse Placement for Colocated MIMO Radar

Publication Year: 2018, Page(s): 1
| | PDF (778 KB)

Multiple input multiple output (MIMO) radar is known for its superiority over conventional radar due to its antenna and waveform diversity. Although higher angular resolution, improved parameter identifiability, and better target detection are achieved, the hardware costs (due to multiple transmitters and multiple receivers) and high energy consumption (multiple pulses) limit the usage of MIMO rad... View full abstract»

• ### Off-Grid DOA Estimation Using Sparse Bayesian Learning in MIMO Radar With Unknown Mutual Coupling

Publication Year: 2018, Page(s): 1
| | PDF (2310 KB)

In the practical radar with multiple antennas, the antenna imperfections degrade the system performance. In this paper, the problem of estimating the direction of arrival (DOA) in multiple-input and multiple-output (MIMO) radar system with unknown mutual coupling effect between antennas is investigated. To exploit the target sparsity in the spatial domain, the compressed sensing (CS)-based methods... View full abstract»

• ### A CPHD approximation based on a discrete-Gamma cardinality model

Publication Year: 2018, Page(s): 1
| | PDF (2887 KB)

The Cardinalized Probability Hypothesis Density (CPHD) filter has become one of the most acclaimed algorithms for multi-target Bayesian filtering due to its ability to accurately estimate the number of objects and the object states in tracking scenarios affected by clutter. The CPHD filter generalizes the Probabilistic Hypothesis Density (PHD) filter by jointly propa- gating the first-order multi-... View full abstract»

• ### Privacy Preserving Collaborative Computing: Heterogeneous Privacy Guarantee and Efficient Incentive Mechanism

Publication Year: 2018, Page(s): 1
| | PDF (1609 KB)

Collaborative computing uses multiple data servers to jointly complete data analysis, e.g., statistical analysis and inference. One major obstruction for it lies in privacy concern, which is directly associated with nodes' participation and the fidelity of received data. Existing privacy-preserving paradigms for cloud computing and distributed data aggregation only provide nodes with homogeneous p... View full abstract»

• ### Optimized Signal Distortion for PAPR Reduction of OFDM Signals with IFFT/FFT Complexity via ADMM Approaches

Publication Year: 2018, Page(s): 1
| | PDF (570 KB)

In this paper, we propose two low-complexity optimization methods to reduce peak-to-average power ratio (PAPR) values of orthogonal frequency division multiplexing (OFDM) signals via alternating direction method of multipliers (ADMM). First, we formulate a non-convex signal distortion optimization model based on minimizing data carrier distortion such that the constraints are placed on PAPR and th... View full abstract»

• ### Joint Independent Subspace Analysis: Uniqueness and Identifiability

Publication Year: 2018, Page(s): 1
| | PDF (1158 KB)

This paper deals with the identifiability of joint independent subspace analysis (JISA). JISA is a recently-proposed framework that subsumes independent vector analysis (IVA) and independent subspace analysis (ISA). Each underlying mixture can be regarded as a dataset; therefore, JISA can be used for data fusion. In this paper, we assume that each dataset is an overdetermined mixture of several mu... View full abstract»

• ### Semiparametric Inference and Lower Bounds for Real Elliptically Symmetric Distributions

Publication Year: 2018, Page(s): 1
| | PDF (461 KB)

This paper has a twofold goal. The first aim is to provide a deeper understanding of the family of the Real Elliptically Symmetric (RES) distributions by investigating their intrinsic semiparametric nature. The second aim is to derive a semiparametric lower bound for the estimation of the parametric component of the model. The RES distributions represent a semiparametric model where the parametric... View full abstract»

• ### Polarization Sensitivity of Antenna Arrays

Publication Year: 2018, Page(s): 1
| | PDF (1132 KB)

The manifold of an array with identical antennas is generally assumed to be insensitive to the polarization of the impinging signal except for a complex scale factor which only affects the signal amplitude. Signal polarization is therefore considered in the literature in the context of diversely polarized arrays which are specifically designed to be sensitive to polarization. In this paper we show... View full abstract»

• ### Computationally Efficient Multi-agent Multi-object Tracking with Labeled Random Finite Sets

Publication Year: 2018, Page(s): 1
| | PDF (1032 KB) |  Media

This paper addresses multi-agent multi-object tracking with labeled random finite sets via Generalized Covariance Intersection (GCI) fusion. While standard GCI fusion of Labeled Multi-Object (LMO) densities is labelwise and hence fully parallelizable, previous work unfortunately revealed that its fusion performance is highly sensitive to the unavoidable label inconsistencies among different agents... View full abstract»

• ### Computationally efficient off-line joint change point detection in multiple time series

Publication Year: 2018, Page(s): 1
| | PDF (5315 KB)

In this paper, a computationally efficient algorithm for Bayesian joint change point (CP) detection (CPD) in multiple time series is presented. The data generation model includes a number of change configurations (CC), each affecting a unique subset of the time series, which introduces correlation between the positions of CPs in the monitored time series. The inference objective is to identify joi... View full abstract»

Publication Year: 2018, Page(s): 1
| | PDF (634 KB)

This paper examines the role of full-duplex radio for securing wireless network from a new perspective. It first studies the secrecy capacity of two single-antenna full-duplex users against a multi-antenna eavesdropper (Eve) who has the perfect knowledge of the channel state information (CSI) from users to Eve. It is shown that if Eve uses a basic matched-filtering (BMF), the probability of zero s... View full abstract»

• ### Non-Iterative MDS Method for Collaborative Network Localization with Sparse Range and Pointing Measurements

Publication Year: 2018, Page(s): 1
| | PDF (1100 KB)

Multi-agent localization is a basic requirement for many networked applications. The particular application to swarming Unmanned Aerial Vehicles (UAV's) or munitions requires spatial coordination of agents, including the ability to assume and maintain a prescribed flight formation. An in-flight awareness of network morphology and node location is therefore needed. While global navigation satellite... View full abstract»

• ### Iterative Channel Estimation Using LSE and Sparse Message Passing for MmWave MIMO Systems

Publication Year: 2018, Page(s): 1
| | PDF (2798 KB)

We propose an iterative channel estimation algorithm based on the Least Square Estimation (LSE) and Sparse Message Passing (SMP) algorithm for the Millimeter Wave (mmWave) MIMO systems. The channel coefficients of the mmWave MIMO are approximately modeled as a Bernoulli-Gaussian distribution and the channel matrix is sparse with only a few non-zero entries. By leveraging the advantage of sparsenes... View full abstract»

• ### Solution and Analysis of TDOA Localization of a Near or Distant Source in Closed-Form

Publication Year: 2018, Page(s): 1
| | PDF (703 KB)

Point positioning and direction of arrival (DOA) localization require separate estimators, depending on the source is near or distant from the sensors. The use of modified polar representation (MPR) for the source location enables the integration of the two to a single estimator, resulting in more direct and accurate processing and, most importantly, eliminating the need of the a priori knowledge ... View full abstract»

• ### A Generalized Multifractal Formalism for the Estimation of Nonconcave Multifractal Spectra

Publication Year: 2018, Page(s): 1
| | PDF (1237 KB)

Multifractal analysis has become a powerful signal processing tool that characterizes signals or images via the fluctuations of their pointwise regularity, quantified theoretically by the so-called multifractal spectrum. The practical estimation of the multifractal spectrum fundamentally relies on exploiting the scale dependence of statistical properties of appropriate multiscale quantities, such ... View full abstract»

• ### Joint Spatiotemporal Multipath Mitigation in Large-Scale Array Localization

Publication Year: 2018, Page(s): 1
| | PDF (414 KB)

Large-scale antenna arrays not only have been considered as the key technology in future communications systems, but also promise revolutionary impacts on wireless localization. In this paper, we determine the effects of multipath propagation on the localization performance using large-scale antenna arrays. Such effects can be mitigated by joint temporal and spatial separation of the multipath sig... View full abstract»

• ### CayleyNets: Graph Convolutional Neural Networks with Complex Rational Spectral Filters

Publication Year: 2018, Page(s): 1
| | PDF (24092 KB)

The rise of graph-structured data such as social networks, regulatory networks, citation graphs, and functional brain networks, in combination with resounding success of deep learning in various applications, has brought the interest in generalizing deep learning models to non-Euclidean domains. In this paper, we introduce a new spectral domain convolutional architecture for deep learning on graph... View full abstract»

• ### iMUSIC: A Family of MUSIC-like Algorithms for Integer Period Estimation

Publication Year: 2018, Page(s): 1
| | PDF (5422 KB)

The MUSIC algorithm is one of the most popular techniques today for line spectral estimation. If the line spectrum is that of a periodic signal, can we adapt MUSIC to exploit the additional harmonicity in the spectrum? Important prior work in this direction includes the Harmonic MUSIC (HMUSIC) algorithm and its variations. For applications where the period of the discrete signal is an integer (or ... View full abstract»

• ### Offset-Based Beamforming: A New Approach to Robust Downlink Transmission

Publication Year: 2018, Page(s): 1
| | PDF (261 KB)

The design of a set of beamformers for the multi-user multiple-input single-output (MISO) downlink that provides the receivers with prespecified levels of quality-of-service (QoS) can be quite challenging when the channel state information is not perfectly known at the base station. The constraint of having the SINR meet or exceed a given threshold with high probability is intractable in general, ... View full abstract»

• ### Secure State Estimation against Integrity Attacks: A Gaussian Mixture Model Approach

Publication Year: 2018, Page(s): 1
| | PDF (5408 KB)

We consider the problem of estimating the state of a linear time-invariant Gaussian system using N sensors, where a subset of the sensors can potentially be compromised by an adversary. In this case, localizing the compromised sensors is of crucial importance for obtaining an accurate state estimate. Inspired by the clustering algorithm in machine learning, we propose a Gaussian-mixture-model-base... View full abstract»

• ### Information Geometric Approach to Multisensor Estimation Fusion

Publication Year: 2018, Page(s): 1
| | PDF (555 KB)

Distributed estimation fusion is concerned with combination of local estimates from multiple distributed sensors to produce a fused result. In this paper, we characterize local estimates as posterior probability densities, and assume that they all belong to a parametric family. Our starting point is to consider this family as a Riemannian manifold by introducing the Fisher information metric. From... View full abstract»

• ### Learning Tensors From Partial Binary Measurements

Publication Year: 2018, Page(s): 1
| | PDF (455 KB)

We generalize the 1-bit matrix completion problem to higher-order tensors. Consider a rank-$r$, order-$d$tensor$T$in$\mathbb{R}^{N} \times \cdots \times \mathbb{R}^{N}$with bounded entries. We show that when$r=O(1)$such a tensor can be estimated effi... 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