EURASIP Journal on Advances in Signal Processing

http://link.springer.com/journal/13634

List of Papers (Total 3,435)

An optimized two-level discrete wavelet implementation using residue number system

Using discrete wavelet transform (DWT) in high-speed signal processing applications imposes a high degree of caution to hardware resource availability, latency and power consumption. In this paper, we investigated the design and implementation aspects of a multiplier-free two-level DWT by using residue number system (RNS). The proposed two-level takes the advantage of performing...

Adaptive reconstruction for azimuth signal of multichannel HRWS SAR imaging system

The reconstruction of azimuth signal in multichannel synthetic aperture radar (SAR) for high-resolution and wide-swath (HRWS) imaging requires exact steering vectors. The information of ambiguities and system parameters are used to create the steering vectors. The knowledge of ambiguities involves ambiguity number and index; the system parameters include the pulse repetition...

Locally optimal detector design in impulsive noise with unknown distribution

This paper designs the locally optimal detector (LOD) in additive white impulsive noise with unknown distribution. Unlike traditional LODs derived from a known or approximated noise probability density function (PDF), the LOD proposed in this paper is achieved by designing the zero-memory non-linearity (ZMNL) function based on real data. After the PDF estimation in a...

On the effect of model mismatch for sequential Info-Greedy Sensing

We characterize the performance of sequential information-guided sensing (Info-Greedy Sensing) when the model parameters (means and covariance matrices) are estimated and inaccurate. Our theoretical results focus on Gaussian signals and establish performance bounds for signal estimators obtained by Info-Greedy Sensing, in terms of conditional entropy (related to the estimation...

Generalized independent low-rank matrix analysis using heavy-tailed distributions for blind source separation

In this paper, statistical-model generalizations of independent low-rank matrix analysis (ILRMA) are proposed for achieving high-quality blind source separation (BSS). BSS is a crucial problem in realizing many audio applications, where the audio sources must be separated using only the observed mixture signal. Many algorithms for solving BSS have been proposed, especially in the...

Deterministic-aided single dataset STAP method based on sparse recovery in heterogeneous clutter environments

Traditional space-time adaptive processing (STAP) usually needs many independent and identically distributed (i.i.d) training datasets for estimating clutter covariance matrix (CCM). But this requirement is hardly satisfied in the heterogeneous clutter environments, which lead to an inaccurate estimation of CCM and accordingly degrade the performance of STAP significantly. To...

Correlation feature-based detector for range distributed target in sea clutter

In this paper, a novel correlation feature-based detector is proposed to deal with the challenging problem of detecting a range-distributed target embedded in nonstationary sea clutter. It is well known that sea clutter consists of a speckle component modulated by texture. The nonstationary property of sea clutter is mainly reflected in texture, but its correlation characteristic...

2-D DOA tracking using variational sparse Bayesian learning embedded with Kalman filter

In this paper, we consider the 2-D direction-of-arrival (DOA) tracking problem. The signals are captured by a uniform spherical array and therefore can be analyzed in the spherical harmonics domain. Exploiting the sparsity of source DOAs in the whole angular region, we propose a novel DOA tracking method to estimate the source locations and trace their trajectories by using the...

Gene regulatory network state estimation from arbitrary correlated measurements

BackgroundAdvancements in gene expression technology allow acquiring cheap and abundant data for analyzing cell behavior. However, these technologies produce noisy, and often correlated, measurements on the transcriptional states of genes. The Boolean network model has been shown to be effective in capturing the complex dynamics of gene regulatory networks (GRNs). It is important...

Backtracking-based dynamic programming for resolving transmit ambiguities in WSN localization

The complexity of agent localization increases significantly when unique identification of the agents is not possible. Corresponding application cases include multiple-source localization, in which the agents do not have identification sequences at all, and scenarios in which it is infeasible to send sufficiently long identification sequences, e.g., for highly resource-limited...

Cramer-Rao bounds in the estimation of time of arrival in fading channels

This paper computes the Cramer-Rao bounds for the time of arrival estimation in a multipath Rice and Rayleigh fading scenario, conditioned to the previous estimation of a set of propagation channels, since these channel estimates (correlation between received signal and the pilot sequence) are sufficient statistics in the estimation of delays. Furthermore, channel estimation is a...

Probability-based pilot allocation for MIMO relay Distributed compressed sensing channel estimation

Multiple-Input Multiple-Output (MIMO) relay communication systems are used as an efficient system in spectral efficiency and power allocation view point. In these systems, some of the facilities need channel state information (CSI). Besides, new estimation methods based on compressed sensing (CS) are well known for their spectral efficiency and accuracy. In this paper, we have...

DL-CHI: a dictionary learning-based contemporaneous health index for degenerative disease monitoring

Effective monitoring of degenerative patient conditions is crucial for many clinical decision-making problems. Leveraging the nowadays data-rich environments in many clinical settings, in this paper, we propose a novel clinical data fusion framework that can build a contemporaneous health index (CHI) for degenerative disease monitoring to quantify the severity of deterioration...

Direction finding with a single spatially stretched vector sensor in the presence of mutual coupling

This paper is concerned with DOA estimation using a single-electromagnetic vector sensor in the presence of mutual coupling. Firstly, we apply the temporally smoothing technique to improve the identifiability limit of a single-vector sensor. In particular, we establish sufficient conditions for constructing temporally smoothed matrices to resolve K > 2 incompletely polarized (IP...

Multiple importance sampling revisited: breaking the bounds

We revisit the multiple importance sampling (MIS) estimator and investigate the bound on the efficiency improvement over balance heuristic estimator with equal count of samples established in Veach’s thesis. We revise the proof for this and come to the conclusion that there is no such bound and henceforth it makes sense to look for new estimators that improve on balance heuristic...

Consensus-based distributed adaptive target tracking in camera networks using Integrated Probabilistic Data Association

In this paper, a novel consensus-based adaptive algorithm for distributed target tracking in large scale camera networks is presented, aimed at situations characterized by limited sensing range, high-level clutter, and possibly occulted targets. The concept of Integrated Probabilistic Data Association (IPDA) is introduced in the distributed adaptive tracker design so that the...

Fast dictionary learning from incomplete data

This paper extends the recently proposed and theoretically justified iterative thresholding and K residual means (ITKrM) algorithm to learning dictionaries from incomplete/masked training data (ITKrMM). It further adapts the algorithm to the presence of a low-rank component in the data and provides a strategy for recovering this low-rank component again from incomplete data...

Improving the conditioning of the optimization criterion in acoustic multi-channel equalization using shorter reshaping filters

In acoustic multi-channel equalization techniques, such as complete multi-channel equalization based on the multiple-input/output inverse theorem (MINT), relaxed multi-channel least-squares (RMCLS), and partial multi-channel equalization based on MINT (PMINT), the length of the reshaping filters is generally chosen such that perfect dereverberation can be achieved for perfectly...

Projective complex matrix factorization for facial expression recognition

In this paper, a dimensionality reduction method applied on facial expression recognition is investigated. An unsupervised learning framework, projective complex matrix factorization (proCMF), is introduced to project high-dimensional input facial images into a lower dimension subspace. The proCMF model is related to both the conventional projective nonnegative matrix...

Using discretization for extending the set of predictive features

To date, attribute discretization is typically performed by replacing the original set of continuous features with a transposed set of discrete ones. This paper provides support for a new idea that discretized features should often be used in addition to existing features and as such, datasets should be extended, and not replaced, by discretization. We also claim that...

Blind sequential detection for sparse ISI channels

We present a computationally efficient blind sequential detection method for data transmitted over a sparse intersymbol interference channel. Unlike blind sequential detection methods designed for general channels, the proposed method exploits the channel sparsity by using estimated channel sparsity to assist in the detection of the transmitted sequence. A Gaussian mixture model...

Adaptive independent sticky MCMC algorithms

Monte Carlo methods have become essential tools to solve complex Bayesian inference problems in different fields, such as computational statistics, machine learning, and statistical signal processing. In this work, we introduce a novel class of adaptive Monte Carlo methods, called adaptive independent sticky Markov Chain Monte Carlo (MCMC) algorithms, to sample efficiently from...

Joint frequency offset, time offset, and channel estimation for OFDM/OQAM systems

Among the multicarrier modulation techniques considered as an alternative to orthogonal frequency division multiplexing (OFDM) for future wireless networks, a derivative of OFDM based on offset quadrature amplitude modulation (OFDM/OQAM) has received considerable attention. In this paper, we propose an improved joint estimation method for carrier frequency offset, sampling time...

Burst transmission symbol synchronization in the presence of cycle slip arising from different clock frequencies

In digital communication systems, different clock frequencies of transmitter and receiver usually are translated into cycle slips. Receivers and transmitters may experience different sampling frequencies due to manufacturing imperfection, Doppler effect introduced by channel or having error in estimation of symbol rate. Timing synchronization in presence of cycle slip for a burst...