# IEEE Signal Processing Letters

## Filter Results

Displaying Results 1 - 25 of 38
• ### Front Cover

Publication Year: 2014, Page(s): C1
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• ### IEEE Signal Processing Letters publication information

Publication Year: 2014, Page(s): C2
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Publication Year: 2014, Page(s):1027 - 1028
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Publication Year: 2014, Page(s):1029 - 1030
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• ### Online Visual Tracking via Two View Sparse Representation

Publication Year: 2014, Page(s):1031 - 1034
Cited by:  Papers (14)
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In this letter, we present a novel online tracking method based on sparse representation. In contrast to existing “sparse representation”-based tracking algorithms, this work adopts the sparse representation method to construct both object and state models. The tracked object can be sparsely represented by a series of object templates, and also can be sparsely represented by candidat... View full abstract»

• ### Saliency Detection with Multi-Scale Superpixels

Publication Year: 2014, Page(s):1035 - 1039
Cited by:  Papers (35)
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We propose a salient object detection algorithm via multi-scale analysis on superpixels. First, multi-scale segmentations of an input image are computed and represented by superpixels. In contrast to prior work, we utilize various Gaussian smoothing parameters to generate coarse or fine results, thereby facilitating the analysis of salient regions. At each scale, three essential cues from local co... View full abstract»

• ### Combination of Cepstral and Phonetically Discriminative Features for Speaker Verification

Publication Year: 2014, Page(s):1040 - 1044
Cited by:  Papers (6)
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Most speaker recognition systems rely on short-term acoustic cepstral features for extracting the speaker-relevant information from the signal. But phonetic discriminant features, extracted by a bottle-neck multi-layer perceptron (MLP) on longer stretches of time, can provide a complementary information and have been adopted in speech transcription systems. We compare the speaker verification perf... View full abstract»

• ### Ghost-Free High Dynamic Range Imaging via Rank Minimization

Publication Year: 2014, Page(s):1045 - 1049
Cited by:  Papers (13)
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We propose a ghost-free high dynamic range (HDR) image synthesis algorithm using a low-rank matrix completion framework, which we call RM-HDR. Based on the assumption that irradiance maps are linearly related to low dynamic range (LDR) image exposures, we formulate ghost region detection as a rank minimization problem. We incorporate constraints on moving objects, i.e., sparsity, connectivity, and... View full abstract»

• ### Exploiting Spectral Regrowth for Channel Identification

Publication Year: 2014, Page(s):1050 - 1053
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In modern communication systems, power amplifiers (PAs) are important components and inherently nonlinear. The nonlinearity of the PA causes bandwidth expansion of the communication signal, often referred to as spectral regrowth, at the PA output. Conventionally, spectral regrowth is treated as a distortion, and a range of compensation and filtering techniques have been considered to mitigate its ... View full abstract»

• ### A Contraction Mapping Approach for Robust Estimation of Lagged Autocorrelation

Publication Year: 2014, Page(s):1054 - 1058
Cited by:  Papers (2)
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We consider the zero-crossing rate (ZCR) of a Gaussian process and establish a property relating the lagged ZCR (LZCR) to the corresponding normalized autocorrelation function. This is a generalization of Kedem's result for the lag-one case. For the specific case of a sinusoid in white Gaussian noise, we use the higher-order property between lagged ZCR and higher-lag autocorrelation to develop an ... View full abstract»

• ### Iterative Recovery of Dense Signals from Incomplete Measurements

Publication Year: 2014, Page(s):1059 - 1063
Cited by:  Papers (2)
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Within the framework of compressed sensing, we consider dense signals, which contain both discrete as well as continuous-amplitude components. We demonstrate by a comprehensive numerical study-to the best of our knowledge the first of its kind in the literature-that dense signals can be recovered from noisy, incomplete linear measurements by simple iterative algorithms that are inspired by or are ... View full abstract»

• ### The Finite Fractional Zak Transform

Publication Year: 2014, Page(s):1064 - 1067
Cited by:  Papers (1)
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We give a matrix form of the Zak transform in the finite setting and show it can be diagonalized with eigenvectors of the two variable time-independent Schröedinger difference equation. Using this diagonalization we produce a fractional Zak transform and illustrate the effect that it has on constant frequencies. View full abstract»

• ### Autoencoder-based Unsupervised Domain Adaptation for Speech Emotion Recognition

Publication Year: 2014, Page(s):1068 - 1072
Cited by:  Papers (36)
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With the availability of speech data obtained from different devices and varied acquisition conditions, we are often faced with scenarios, where the intrinsic discrepancy between the training and the test data has an adverse impact on affective speech analysis. To address this issue, this letter introduces an Adaptive Denoising Autoencoder based on an unsupervised domain adaptation method, where p... View full abstract»

• ### On the Projection of PLLRs for Unbounded Feature Distributions in Spoken Language Recognition

Publication Year: 2014, Page(s):1073 - 1077
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The so called Phone Log-Likelihood Ratio (PLLR) features have been recently introduced as a novel and effective way of retrieving acoustic-phonetic information in spoken language and speaker recognition systems. In this letter, an in-depth insight into the PLLR feature space is provided and the multidimensional distribution of these features is analyzed in a language recognition system. The study ... View full abstract»

• ### Asynchronous Transmitter Position and Velocity Estimation Using A Dual Linear Chirp

Publication Year: 2014, Page(s):1078 - 1082
Cited by:  Papers (3)
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We present a closed-form least squares algorithm for estimating the position and velocity of a source, asynchronously transmitting known dual linear chirp signals, given times of arrival measurements obtained by spatially distributed sensors. The estimates involve less computational load compared to the optimal maximum likelihood estimates. Simulations show that the proposed estimates have similar... View full abstract»

• ### Cramér–Rao Bounds for Broadband Dispersion Extraction of Borehole Acoustic Modes

Publication Year: 2014, Page(s):1083 - 1087
Cited by:  Papers (1)
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The estimation of slowness (the reciprocal of velocity) and attenuation dispersion of borehole acoustic and surface seismic data is key to a variety of applications. The emerging broadband approach for dispersion extraction of multiple modes has shown significant advantages over traditional narrowband approaches. In this letter, Cramér-Rao bounds (CRBs) are established to characterize the ... View full abstract»

• ### Frequency-Domain Volterra Filter Based on Data-Driven Soft Decision for Nonlinear Acoustic Echo Suppression

Publication Year: 2014, Page(s):1088 - 1092
Cited by:  Papers (1)  |  Patents (1)
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In this letter, we propose a novel frequency-domain second-order Volterra filter based on soft decision for nonlinear acoustic echo suppression. This letter offers an efficient algorithm for nonlinear echo power estimation using the second-order Volterra filter and an AES algorithm using the estimated nonlinear echo power spectrum within a soft decision baseline by incorporating the ratio of the a... View full abstract»

• ### An Explicit Solution for Target Localization in Noncoherent Distributed MIMO Radar Systems

Publication Year: 2014, Page(s):1093 - 1097
Cited by:  Papers (13)
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This work focuses on the moving target localization problem in the noncoherent multiple-input multiple-output radar system with widely separated antennas. We assume that the time delay and Doppler shift between each transmit/receive element pair have already been measured by a preprocessing algorithm. Utilizing these measurements, an explicit method for jointly estimating the target position and v... View full abstract»

• ### Blind Modulation Classification Algorithm for Single and Multiple-Antenna Systems Over Frequency-Selective Channels

Publication Year: 2014, Page(s):1098 - 1102
Cited by:  Papers (12)
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This letter proposes a blind modulation classification (MC) algorithm applicable to single and multiple-antenna systems operating over frequency-selective channels. We show that the correlation functions of the received signals for certain modulation formats exhibit peaks at a particular set of time lags, a result which can be exploited as a discriminating feature. We also develop a new hypothesis... View full abstract»

• ### Asymptotic Error Bounds on Prediction of Narrowband MIMO Wireless Channels

Publication Year: 2014, Page(s):1103 - 1107
Cited by:  Papers (1)
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In this letter, we derive simple expressions for the lower bound on the prediction error variance for narrowband MIMO channel with uniform linear array at both ends of the link. The derived bounds show the relationship between the achievable prediction performance and prediction algorithm design parameters, thereby providing useful insights into the development of fading channel prediction algorit... View full abstract»

• ### Continuous Mixed $p$-Norm Adaptive Algorithm for System Identification

Publication Year: 2014, Page(s):1108 - 1110
Cited by:  Papers (9)
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We propose a new adaptive filtering algorithm in system identification applications which is based on a continuous mixed p-norm. It enjoys the advantages of various error norms since it combines p-norms for 1 ≤ p ≤ 2. The mixture is controlled by a continuous probability density-like function of p which is assumed to be uniform in our derivations in this letter. Two versions of the s... View full abstract»

• ### Nested Array Processing for Distributed Sources

Publication Year: 2014, Page(s):1111 - 1114
Cited by:  Papers (12)
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We consider the problem of using linear nested arrays to estimate the directions of arrival (DOAs) of distributed sources and to detect the source number, where we have more sources than actual physical sensors. Angular spread, caused by the multipath nature of the distributed sources, makes the commonly used point-source assumption challenging. We establish the signal model for distributed source... View full abstract»

• ### Language-Independent Text-Line Extraction Algorithm for Handwritten Documents

Publication Year: 2014, Page(s):1115 - 1119
Cited by:  Papers (7)
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Text-line extraction in handwritten documents is an important step for document image understanding, and a number of algorithms have been proposed to address this problem. However, most of them exploit features of specific languages and work only for a given language. In order to overcome this limitation, we develop a language-independent text-line extraction algorithm. Our method is based on conn... View full abstract»

• ### Convolutional Neural Networks for Distant Speech Recognition

Publication Year: 2014, Page(s):1120 - 1124
Cited by:  Papers (37)
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We investigate convolutional neural networks (CNNs) for large vocabulary distant speech recognition, trained using speech recorded from a single distant microphone (SDM) and multiple distant microphones (MDM). In the MDM case we explore a beamformed signal input representation compared with the direct use of multiple acoustic channels as a parallel input to the CNN. We have explored different weig... View full abstract»

• ### Group Sparsity via SURE Based on Regression Parameter Mean Squared Error

Publication Year: 2014, Page(s):1125 - 1129
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Any regularization method requires the selection of a penalty parameter and many model selection criteria have been developed based on various discrepancy measures. Most of the attention has been focused on prediction mean squared error. In this paper we develop a model selection criterion based on regression parameter mean squared error via SURE (Stein's unbiased risk estimator). We then apply th... View full abstract»

## Aims & Scope

The IEEE Signal Processing Letters is a monthly, archival publication designed to provide rapid dissemination of original, cutting-edge ideas and timely, significant contributions in signal, image, speech, language and audio processing.

Full Aims & Scope

## Meet Our Editors

Editor-in-Chief
James E. Fowler
Dept Electrical & Computer Engineering
Associate Director
Distributed Analytics and Security Institute
Mississippi State University
Mississippi State, MS 39762 USA
fowler@ece.msstate.edu