IEEE Transactions on Signal Processing

In this paper, we formulate Gaussian process regression with observations under the localization uncertainty due to the resource-constrained sensor networks. In our formulation, effects of observations, measurement noise, localization uncertainty, and ...

We formally generalize the sign-definiteness lemma to the case of complex-valued matrices and multiple norm-bounded uncertainties. This lemma has found many applications in the study of the stability of control systems, and in the design and ...

A low complexity, essentially-ML decoding technique for the Golden code and the three antenna Perfect code was introduced by Sirianunpiboon, Howard and Calderbank. Though no theoretical analysis of the decoder was given, the simulations showed that this ...

We consider the smoothing problem for a general state space system using sequential Monte Carlo (SMC) methods. The marginal smoother is assumed to be available in the form of weighted random particles from the SMC output. New algorithms are developed to ...

A common simplification in the statistical treatment of linear time-varying (LTV) wireless channels is the approximation of the channel as a stationary random process inside certain time-frequency regions. We develop a methodology for the determination ...

Polar codes are a recently discovered family of capacity-achieving codes that are seen as a major breakthrough in coding theory. Motivated by the recent rapid progress in the theory of polar codes, we propose a semi-parallel architecture for the ...

We consider decentralized detection through distributed sensors that perform level-triggered sampling and communicate with a fusion center (FC) via noisy channels. Each sensor computes its local log-likelihood ratio (LLR), samples it using the level-...

This paper is concerned with the $H_{\infty}$ fixed-interval smoothing estimation for time-delay systems which include continuous-time case and discrete-time case. In the case of discrete-time systems, the problem can be solved by using the conventional ...

This paper investigates quantization of channel state information (CSI) and bit allocation across wireless links in a multi-source, single-relay cooperative cellular network. Our goal is to minimize the loss in performance, measured as the achievable ...

In this work, a Bayesian approximate message passing algorithm is proposed for solving the multiple measurement vector (MMV) problem in compressive sensing, in which a collection of sparse signal vectors that share a common support are recovered from ...

A common approach to study the relationship between different signals is to model them as random processes and estimate their joint probability distribution from the observed data. When synchronous samples of the random processes are available, then the ...

Despite an increased interest in complex independent component analysis (ICA) during the last two decades, a closed form expression for the Cramér-Rao bound (CRB) for the demixing matrix is not known yet. In this paper, we fill this gap by deriving a ...

Savitzky-Golay (S-G) filters are finite impulse response lowpass filters obtained while smoothing data using a local least-squares (LS) polynomial approximation. Savitzky and Golay proved in their hallmark paper that local LS fitting of polynomials and ...

This correspondence presents a novel method for simultaneous tracking of multiple non-stationary targets in video. Our method operates directly on the video data and does not require any detection. We propose a multi-target likelihood function for the ...

Orthogonal Matching Pursuit (OMP) is a canonical greedy pursuit algorithm for sparse approximation. Previous studies of OMP have considered the recovery of a sparse signal ${\mbi {x}}$ through ${\mmb {\Phi}}$ and ${\mbi {y}}={\mmb {\Phi}} {\mbi {x}}+{\...

The application of particle filters to real-time systems is often limited because of their computational complexity, and hence the use of graphics processing units (GPUs) that contain hundreds of processing elements on a chip is very promising. However, ...

In many signal and image processing applications, a desired clean signal is distorted from blur and noise. Reconstructing the clean signal usually yields to a high dimensional ill-conditioned system of equations, where a direct solution would severely ...

This paper considers the problem of sparse signal recovery when the decoder has prior information on the sparsity pattern of the data. The data vector ${\bf x}=[x_{1},\ldots,x_{N}]^{T}$ has a randomly generated sparsity pattern, where the $i$-th entry ...

As the feature size of NAND flash memory decreases, the threshold voltage signal becomes less reliable, and its distribution varies significantly with the number of program-erase (PE) cycles and the data retention time. We have developed parameter ...

This paper develops a framework for the estimation of a time-varying random signal using a distributed sensor network. Given a continuous time model sensors collect noisy observations and produce local estimates according to the discrete time equivalent ...

This paper addresses the optimal cooperative beamforming design for multi-user multi-relay wireless networks in which the single-carrier frequency division multiple access (SC-FDMA) technique is employed at the terminals. The problem of interest is to ...

Spectral unmixing is an important issue to analyze remotely sensed hyperspectral data. Although the linear mixture model has obvious practical advantages, there are many situations in which it may not be appropriate and could be advantageously replaced ...

Co-clustering is a generalization of unsupervised clustering that has recently drawn renewed attention, driven by emerging data mining applications in diverse areas. Whereas clustering groups entire columns of a data matrix, co-clustering groups columns ...

We investigate how to design space-time block codes for multiple access channels with full diversity and low decoding complexity for any number of transmitters and one receiver with quantized feedback. We provide the details of our scheme for four ...