# IET Signal Processing

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• ### Application of linear canonical transform correlation for detection of linear frequency modulated signals

Publication Year: 2016, Page(s):351 - 358
| | PDF (270 KB)

Linear canonical transform (LCT), which can be deemed to be a generalisation of the fractional Fourier transform, has been used in several areas, including signal processing and optics. Motivated by the operator theory, a new unitary operator associated with the LCT is introduced. This new operator generalises the unitary fractional operator which is proposed by Akay et al. recently. Via op... View full abstract»

• ### LMMSE channel estimation in OFDM context: a review

Publication Year: 2017, Page(s):123 - 134
| | PDF (4596 KB)

Linear minimum mean square error (LMMSE) is by definition the optimal channel estimator in the sense of mean square error criterion, but its practical application is limited by its high complexity. Furthermore, the LMMSE estimation method requires the knowledge of both the channel and the noise statistics, which are a priori unknown at the receiver. A wide range of techniques are proposed in the l... View full abstract»

• ### Subcarrier and power allocation scheme for downlink OFDM-NOMA systems

Publication Year: 2017, Page(s):51 - 58
| | PDF (2291 KB)

In this study, the authors investigate the resource allocation (RA) problem for the downlink orthogonal frequency division multiplexing based non-orthogonal multiple access (OFDM-NOMA) system. The RA problem is decomposed into two subproblems of subcarrier allocation (SA) and power allocation (PA). For the SA, a user grouping based greedy algorithm is proposed under the assumption that power is un... View full abstract»

• ### Clutter suppression and GMTI for hypersonic vehicle borne SAR system with MIMO antenna

Publication Year: 2017, Page(s):909 - 915
| | PDF (3849 KB)

This study proposes a clutter suppression approach and the corresponding ground moving target imaging algorithm for hypersonic vehicle (HSV) borne synthetic aperture radar (SAR) system with multiple-input-multiple-output (MIMO) antenna. HSV-borne radar platforms fly with a high speed, which can lead to severe Doppler ambiguity, and the radar system usually cannot provide enough channel freedom deg... View full abstract»

• ### Modified Volterra LMS algorithm to fractional order for identification of Hammerstein non-linear system

Publication Year: 2017, Page(s):975 - 985
| | PDF (3931 KB)

In this study, a new non-linear recursive mechanism for Volterra least mean square (VLMS) algorithm is proposed in the domain of non-linear adaptive signal processing and control. The proposed adaptive scheme is developed by applying concepts and theories of fractional calculus in weight adaptation structure of standard VLMS approach. The design scheme based on fractional VLMS (F-VLMS) algorithm i... View full abstract»

• ### Music emotion recognition using PSO-based fuzzy hyper-rectangular composite neural networks

Publication Year: 2017, Page(s):884 - 891
| | PDF (1835 KB)

This study proposed a novel system for recognising emotional content in music, and the proposed system is based on particle swarm optimisation (PSO)-based fuzzy hyper-rectangular composite neural networks (PFHRCNNs), which integrates three computational intelligence tools, i.e. hyper-rectangular composite neural networks (HRCNNs), fuzzy systems, and PSO. PFHRCNN is flexible to the complex data due... View full abstract»

• ### Bidirectional wireless information and power transfer for decode-and-forward relay systems

Publication Year: 2017, Page(s):1015 - 1020
| | PDF (2056 KB)

In this study, the authors investigate the bidirectional wireless information and power transfer (BWIPT) in decode-and-forward (DF) relay systems, where the bidirectional relay can decode and forward information from the user to the access point (AP), and assist the wireless power transfer from the AP to the user. The relay employs the power splitting (PS) protocol to coordinate the received signa... View full abstract»

• ### Unsupervised noise removal technique based on constrained NMF

Publication Year: 2017, Page(s):788 - 795
| | PDF (4274 KB)

This paper presents a novel approach to mitigate background interference noise in a noisy audio environment based on unsupervised speech enhancement without the prior knowledge of speech as well as noise signal. In this scheme, a noisy speech signal is represented by a non-negative matrix factorisation (NMF) with sparseness constraints. Using NMF with constraints, noise density spectrum is estimat... View full abstract»

• ### Cooperative spectrum estimation over large-scale cognitive radio networks

Publication Year: 2017, Page(s):1006 - 1014
| | PDF (2630 KB)

Spectrum sensing is a significant issue in cognitive radio networks which enables estimation of the frequency spectrum and hence provides frequency reuse. In the large-scale cognitive radio networks, secondary users cannot share a common spectrum since the coverage area of primary users is limited. In this study, the authors suggest a diffusion adaptive learning algorithm based on correntropy coop... View full abstract»

• ### Mℓ1,2-MUSIC algorithm for DOA estimation of coherent sources

Publication Year: 2017, Page(s):429 - 436
| | PDF (3554 KB)

Recasting the direction of arrival (DOA) estimation problem into sparse model is a subject of many researches, which has been carried out by different methods. Using the compressive sensing (CS) multiple measurement vector recovery algorithms have improved the resolution of DOA estimation in comparison with conventional methods such as multiple signal classification (MUSIC). In addition, a recentl... View full abstract»

• ### Power allocation scheme and spectral efficiency analysis for downlink non-orthogonal multiple access systems

Publication Year: 2017, Page(s):537 - 543
| | PDF (2365 KB)

In this study, the authors investigate the power allocation (PA) problem and spectral efficiency (SE) analysis for the single antenna downlink non-orthogonal multiple access (NOMA) system under the sum rate maximising criteria with minimum rate constraints (SRMC-MRC). For the PA problem, they propose the duality scheme for SRMC-MRC which is considered as the optimal solution for the PA problem on ... View full abstract»

• ### Acoustic vector sensor: reviews and future perspectives

Publication Year: 2017, Page(s):1 - 9
| | PDF (3673 KB)

Acoustic vector sensor (AVS) has been recently researched and developed for acoustic wave capturing and signal processing. Conventional array generally employs spatially displayed sensors for signal enhancement, source localisation, target tracking, etc. However, the large size usually limits its implementations on some portable devices. AVS which generally includes one omni-directional sensor and... View full abstract»

• ### Deep neural network-based linear predictive parameter estimations for speech enhancement

Publication Year: 2017, Page(s):469 - 476
| | PDF (5888 KB)

This study presents a speech enhancement technique to improve noise corrupted speech via deep neural network (DNN)-based linear predictive (LP) parameter estimations of speech and noise. With regard to the LP coefficient estimation, an enhanced estimation method using a DNN with multiple layers was proposed. Excitation variances were then estimated via a maximum-likelihood scheme using observed no... View full abstract»

• ### Message passing detection for large-scale MIMO systems: damping factor analysis

Publication Year: 2017, Page(s):923 - 935
| | PDF (9901 KB)

A message passing detector based on belief propagation (BP) algorithm for Markov random fields (MRF-BP) and factor graph (FG-BP) graphical models is analysed under different large-scale (LS) multiple-input multiple-output (MIMO) scenarios, including system parameters, such as damping factor (DF), number of users and number of antennas, from N=20 to 200 antennas. Specifically, the DF variation unde... View full abstract»

• ### Single Channel speech separation based on empirical mode decomposition and Hilbert Transform

Publication Year: 2017, Page(s):579 - 586
| | PDF (4407 KB)

In this study, the authors discuss unsupervised separation of two speakers from single microphone recording using empirical mode decomposition (EMD) and Hilbert transform (HT) generally known as Hilbert-Huang transform. A two-stage separation procedure is proposed for single-channel (SC) speech separation. Initial stage of separation is done using EMD, HT and instantaneous frequencies. EMD decompo... View full abstract»

• ### Low-complexity graph-based turbo equalisation for single-carrier and multi-carrier FTN signalling

Publication Year: 2017, Page(s):838 - 845
| | PDF (3381 KB)

The authors propose a novel turbo detection scheme based on the factor graph (FG) serial-schedule belief propagation equalisation algorithm with low complexity for single-carrier faster-than-Nyquist (SC-FTN) and multi-carrier FTN (MC-FTN) signalling. In this work, the additive white Gaussian noise channel and multi-path fading channels are both considered. The iterative FG-based equalisation algor... View full abstract»

• ### Digital constant-envelope modulation scheme for radar using multicarrier OFDM signals

Publication Year: 2017, Page(s):861 - 868
| | PDF (3872 KB)

Multicarrier signals using orthogonal frequency division multiplexing (OFDM) bring many advantages to radar such as low probability of intercept, improved target detection performance, optimisation of both radar transmitter and receiver etc. A major drawback of multicarrier OFDM signals is their high peak-to-mean envelope power ratio, which reduces the working efficiency of the used power amplifie... View full abstract»

• ### Source recovery of underdetermined blind source separation based on SCMP algorithm

Publication Year: 2017, Page(s):877 - 883
| | PDF (3078 KB)

In this study, a new algorithm subspace complementary matching pursuit (SCMP) is developed for source recovery of underdetermined blind source separation. The proposed SCMP is more simplified than the conventional complementary matching pursuit (CMP) algorithm. SCMP algorithm selects more than one atom in each iteration to reduce computational complexity, and replaces the l2 norm... View full abstract»

• ### Blind deblurring from single motion image based on adaptive weighted total variation algorithm

Publication Year: 2016, Page(s):611 - 618
| | PDF (1030 KB)

Blind image deblurring is an important topic which is widely used in many research fields such as photography, optics, astronomy, medical images, monitoring, military and so on. Although many algorithms have been proposed to improve the deblurring result in the past years, most of them cannot perform perfectly in some challenging cases. This study presents a novel blind deblurring method based on ... View full abstract»

• ### Time differences of arrival estimation of mixed interference signals using blind source separation based on wireless sensor networks

Publication Year: 2016, Page(s):924 - 929
| | PDF (2762 KB)

The estimation of the time differences of arrival (TDOAs) is significant in passive source localisation systems. The TDOA estimation accuracy may directly affect the source location performance. For co-frequency interference environments, the authors address the problem of the passive blind estimation of time-delays for uncorrelated interference source signals based on wireless sensor networks. Th... View full abstract»

• ### Prediction filter design for active noise cancellation headphones

Publication Year: 2013, Page(s):497 - 504
Cited by:  Papers (5)
| | PDF (611 KB)

Digital active noise control (ANC) for headphones usually has to predict the noise because of the latency of common audio converters. In adaptive feedback ANC, the prediction is based on the noise that entered the headphone. This noise is low-pass filtered because of the physical barrier of the ear cups. In this study, this low-pass characteristic is exploited to define a prediction filter which d... View full abstract»

• ### Fractional bispectrum transform: definition and properties

Publication Year: 2017, Page(s):901 - 908
| | PDF (3766 KB)

A signal with discrete frequency components has a zero bispectrum if no addition or subtraction of any of the frequencies equals one of the frequency components. The authors introduce the fractional bispectrum (FBS) transform in which for signals with zero bispectrum the FBS could be non-zero. It is shown that FBS has the same property as the bispectrum for signals with a Gaussian probability dens... View full abstract»

• ### Sparsity-based STAP algorithm with multiple measurement vectors via sparse Bayesian learning strategy for airborne radar

Publication Year: 2017, Page(s):544 - 553
| | PDF (7384 KB)

To improve the performance of the recently developed parameter-dependent sparse recovery (SR) space-time adaptive processing (STAP) algorithms in real-world applications, the authors propose a novel clutter suppression algorithm with multiple measurement vectors (MMVs) using sparse Bayesian learning (SBL) strategy. First, the necessary and sufficient condition for uniqueness of sparse solutions to... View full abstract»

• ### Performance guarantees of signal recovery via block-OMP with thresholding

Publication Year: 2017, Page(s):952 - 960
| | PDF (2020 KB)

Block-sparsity is an extension of the ordinary sparsity in the realm of the sparse signal representation. Exploiting the block structure of the sparsity pattern, recovery may be possible under more general conditions. In this study, a block version of the orthogonal matching pursuit with thresholding (block-OMPT) algorithm is proposed. Compared with the block version of the orthogonal matching pur... View full abstract»

• ### Compressive sensing for cluster structured sparse signals: variational Bayes approach

Publication Year: 2016, Page(s):770 - 779
| | PDF (1076 KB)

Compressive sensing (CS) provides a new paradigm of sub-Nyquist sampling which can be considered as an alternative to Nyquist sampling theorem. In particular, providing that signals are with sparse representations in some domain, information can be perfectly preserved even with small amount of measurements captured by random projections. Besides sparsity prior of signals, the inherent structure pr... View full abstract»

• ### Sparsity-aware adaptive block-based compressive sensing

Publication Year: 2017, Page(s):36 - 42
| | PDF (6299 KB)

Conventional methods for block-based compressive sensing consider an equal number of samples for all blocks. However, the sparsity order of blocks in natural images could be different and, therefore, a various number of samples could be required for their reconstruction. In this study, the authors propose an adaptive block-based compressive sensing scheme, which collects a different number of samp... View full abstract»

• ### Geometric means and medians with applications to target detection

Publication Year: 2017, Page(s):711 - 720
| | PDF (7835 KB)

This study explores the application of geometric measures-based means and medians on the Riemannian manifold of Hermitian positive-definite (HPD) matrix to target detection problems in radar systems. Firstly, the slow-time dimension of radar received clutter data in each cell is modelled and mapped to HPD matrix space, which can be described as a complex Riemannian manifold. Each point of this man... View full abstract»

• ### Improved single channel phase-aware speech enhancement technique for low signal-to-noise ratio signal

Publication Year: 2016, Page(s):641 - 650
Cited by:  Papers (1)
| | PDF (940 KB)

In the state-of-the-art single channel speech enhancement techniques, the short-time spectral amplitude is modified while the effect of the phase corruption due to the contamination of additive noise is neglected. This study introduces an improved speech enhancement algorithm based on a phase-aware multi-band spectral subtraction technique which estimates the spectral amplitude of the clean speech... View full abstract»

• ### Game-theoretic beamforming techniques for multiuser multi-cell networks under mixed quality of service constraints

Publication Year: 2017, Page(s):631 - 639
| | PDF (4787 KB)

The authors propose a game-theoretic approach for the downlink beamformer design for a multiuser multi-cell wireless network under a mixed quality of services (QoS) criterion. The network has real time users (RTUs) that must attain a specific set of signal-to-interference-plus-noise ratios (SINRs), and non-RTUs whose SINRs should be balanced and maximised. They propose a mixed QoS strategic non-co... View full abstract»

• ### Auction-based competition of hybrid small cells for dropped macrocell users

Publication Year: 2017, Page(s):695 - 703
| | PDF (3561 KB)

We propose an auction-based beamforming and user association algorithm for a wireless network consisting of a macrocell and multiple small cell access points (SCAs). The SCAs compete for serving the macrocell base station (MBS) users (MUs). The corresponding user association problem is solved by the proposed bid-wait auction method. The authors considered two scenarios. In the first scenario, the ... View full abstract»

• ### Novel feature extraction method for cough detection using NMF

Publication Year: 2017, Page(s):515 - 520
| | PDF (2919 KB)

Cough is a common symptom in respiratory diseases. To provide valuable clinical information for cough diagnosis and monitoring, objectively evaluating the quantity and intensity of cough based on cough detection by pattern recognition technologies is needed. Cough detection aims to extract the boundaries of cough events from an audio stream. From spectral visualisation, it is found that the energy... View full abstract»

• ### Wavelet DT method for water leak-detection using a vibration sensor: an experimental analysis

Publication Year: 2017, Page(s):396 - 405
| | PDF (4620 KB)

In this study, the authors propose and analyse a novel leak-detection method based on the `Haar' continuous wavelet transform (CWT) and a double thresholding, i.e. CWTDT. Inspired by the idea of the binary integration technique in radar target detection, the algorithm analyses the non-stationary vibration signal issued from a water pipeline through which it decides whether or not there exists a le... View full abstract»

• ### Robust maximum signal fraction analysis for blind source separation

Publication Year: 2017, Page(s):969 - 974
| | PDF (2090 KB)

Blind source separation (BSS) is an active research topic in the fields of biomedical signal processing and brain-computer interface. As a representative technique, maximum signal fraction analysis (MSFA) has been recently developed for the problem of BSS. However, MSFA is formulated based on the L2-norm, and thus is prone to be negatively affected by outliers. In this study, the authors propose a... View full abstract»

• ### Design and evaluation of symmetric space–time adaptive processing of an array antenna for precise global navigation satellite system receivers

Publication Year: 2017, Page(s):758 - 764
| | PDF (3316 KB)

The most effective method for overcoming the interference vulnerability of global navigation satellite system (GNSS) receivers is to use an adaptive array antenna which has the capability of nulling or beamforming to a certain direction. The space–time adaptive processing (STAP) algorithm, which is very effective in signal processing of the array antenna for anti-interference, is studied. T... View full abstract»

• ### Rhythm-based features for classification of focal and non-focal EEG signals

Publication Year: 2017, Page(s):743 - 748
| | PDF (2609 KB)

Electroencephalogram (EEG) contains five rhythms, which provide details about various activities of brain. These rhythms are separated using Hilbert–Huang transform for classification of focal and non-focal EEG signals. For this, the EEG signal is disintegrated into narrow bands intrinsic mode functions (IMFs) using empirical mode decomposition, and analytic representation of IMFs is comput... View full abstract»

• ### Class of digital integrators and differentiators

Publication Year: 2011, Page(s):251 - 260
Cited by:  Papers (18)
| | PDF (647 KB)

A novel class of 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 then obtained by inverting the transfer functions of the obtained integrators and stabilising the resulting transfer functions together with magnitude compensation if neces... View full abstract»

• ### Oblique projection for direction-of-arrival estimation of hybrid completely polarised and partially polarised signals with arbitrary polarimetric array configuration

Publication Year: 2017, Page(s):893 - 900
| | PDF (3133 KB)

This study deals with the direction-of-arrival (DOA) estimation problem for hybrid completely polarised (CP) and partially polarised (PP) source signals using arbitrary polarimetric antenna arrays. An oblique projection-based polarisation insensitive direction estimation (OPPIDE) algorithm is proposed by exploiting the spatial-sparsity property of the sources. The OP technique is utilised to provi... View full abstract»

Publication Year: 2017, Page(s):622 - 630
| | PDF (3459 KB)

By employing the MIMO (multiple-input-multiple-output) technology in radar, some new problems emerged, that, in order to benefit the MIMO gains in radar, it was necessary to solve them suitably. One of such obstacles is determining the positions of receive antennas in a MIMO radar system with widely separated antennas (WS MIMO radar), since it is shown that the antennas' positions affect the whole... View full abstract»

• ### Non-parallel training for voice conversion using background-based alignment of GMMs and INCA algorithm

Publication Year: 2017, Page(s):998 - 1005
| | PDF (3421 KB)

Most of the voice conversion (VC) researches have used parallel training corpora to train the conversion function. However, in practice it is not always possible to gather parallel corpora, so the need for non-parallel training methods arises. As a successful non-parallel method, nearest neighbour search step and a conversion step alignment method (INCA) algorithm has attracted a lot of attention ... View full abstract»

• ### Performance analysis of filter bank multicarrier system with non-linear high power amplifiers for 5G wireless networks

Publication Year: 2017, Page(s):66 - 72
| | PDF (3772 KB)

The filter bank multicarrier (FBMC) with offset quadrature amplitude modulation (OQAM) is one of the alternative modulation schemes to orthogonal frequency division multiplexing for next generation broadband wireless access systems. The non-linearity of high-power amplifiers (HPA) has a crucial effect on the performance of FBMC systems. In this study, the impacts of non-linear distortion effects a... View full abstract»

• ### Networked $H_\infty$H∞ filtering for Markovian jump T–S fuzzy systems with imperfect premise matching

Publication Year: 2017, Page(s):304 - 312
| | PDF (1257 KB)

This study focuses on networked H∞ fuzzy filtering for Markovian jump Takagi-Sugeno (T-S) fuzzy systems. Since the traditional PDC method is ineffective under network environments, a flexible filter design method is provided with imperfect premise matching. First, a unified T-S fuzzy error model is provided by considering the mismatched grades of membership. Second, by use... View full abstract»

• ### Alternating projection for sparse recovery

Publication Year: 2017, Page(s):135 - 144
| | PDF (4556 KB)

Reconstructing the sparse signal from a few linear measurements has attracted increasing attentions in recent years. In this study, the authors propose the alternating projection (AP) method for sparse signal recovery with learning the sparsity of the original signal. Different with classical hard thresholding algorithms, the AP method regards the signal recovery problem as finding an intersect po... View full abstract»

• ### Common spatial pattern method for real-time eye state identification by using electroencephalogram signals

Publication Year: 2017, Page(s):936 - 941
| | PDF (3465 KB)

Cross-channel maximum and minimum are used to monitor real-time electroencephalogram signals in 14 channels. On detection of a possible change, multivariate empirical mode decomposed the last 2 s of the signal into narrow-band intrinsic mode functions. Common spatial pattern is then utilised to create discriminating features for classification purpose. Logistic regression, artificial neural networ... View full abstract»

• ### Adaptive consensus-based distributed state estimator for non-linear systems in the presence of multiplicative noise

Publication Year: 2017, Page(s):986 - 997
| | PDF (1405 KB)

The problem of consensus-based distributed state estimation of a non-linear dynamical system in the presence of multiplicative observation noise is investigated in this study. Generalised extended information filter (GEIF) is developed for non-linear state estimation in the information-space framework. To fuse the information contribution of local estimators, an average consensus algorithm is empl... View full abstract»

• ### Efficient design of prototype filter for large scale filter bank-based multicarrier systems

Publication Year: 2017, Page(s):521 - 526
| | PDF (1536 KB)

This study presents a new property of the filter bank-based multicarrier (FBMC) system. Also, an efficient iterative algorithm for designing the system with a large number of subcarriers and a prototype filter with a very long length are proposed. For the system, the compact from conditions are derived for both the intersymbol interference free and the interchannel interference (ICI) free. Based o... View full abstract»

• ### Track-before-detect algorithm based on dynamic programming for multi-extended-targets detection

Publication Year: 2017, Page(s):674 - 686
| | PDF (11004 KB)

In recent years, multi-extended-targets detection in sea clutter has gained a special interest. Dynamic programming based track-before-detect (DP-TBD) algorithm is used to detect extended targets in video data of high resolution radars. Two innovations are presented in this work. First one is a novel partition method to cluster targets into well separate groups for the problem of high-dimensional ... View full abstract»

• ### Micro-Doppler analysis of wheels and pedestrians in ISAR imaging

Publication Year: 2008, Page(s):301 - 311
Cited by:  Papers (23)
| | PDF (1099 KB)

In radar imaging, it is well known that relative motion or deformations of parts of illuminated objects induce additional features in the Doppler frequency spectrum. These features are called micro-Doppler effect and appear as sidebands around the central Doppler frequency. They can provide valuable information about the structure of the moving parts and may be used for identification purposes. Pr... View full abstract»

• ### Sensor selection based on maximum entropy fuzzy clustering for target tracking in large-scale sensor networks

Publication Year: 2017, Page(s):613 - 621
| | PDF (2376 KB)

This study proposes a sensor selection approach based on maximum entropy fuzzy clustering to address the target tracking problem in large-scale sensor networks. The authors try to deal with this problem at two levels: (i) sensor-level tracking: data association problem and sensor-level tracking are carried out at the local level, and only the track outputs are transmitted to the fusion centre for ... View full abstract»

• ### Two-dimensional DOA estimation for L-shaped array with nested subarrays without pair matching

Publication Year: 2016, Page(s):1112 - 1117
| | PDF (1971 KB)

Non-uniform L-shaped array consisting of two nested arrays and its computationally efficient two-dimensional direction-of-arrival (DOA) estimation method are developed in this study. The basic idea of the proposed method is to utilise the property of nested arrays and the conjugate symmetry property of the signal auto-correlation function for different time lags to construct a conjugate augmented ... View full abstract»

• ### Universal audio steganalysis based on calibration and reversed frequency resolution of human auditory system

Publication Year: 2017, Page(s):916 - 922
| | PDF (2971 KB)

Calibration and higher-order statistics are standard components of image steganalysis. However, these techniques have not yet found adequate attention in audio steganalysis. Specifically, most of current studies are either non-calibrated or only based on noise removal. The goal of this study is to fill these gaps and to show that calibrated features based on re-embedding technique improve performa... View full abstract»

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IET Signal Processing publishes novel contributions in signal processing.

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