# IET Signal Processing

## Filter Results

Displaying Results 1 - 15 of 15
• ### Directional splitting of Gaussian density in non-linear random variable transformation

Publication Year: 2018, Page(s):1073 - 1081
| | PDF (2019 KB)

Transformation of a random variable is a common need in a design of many algorithms in signal processing, automatic control, and fault detection. Typically, the design is tied to an assumption on a probability density function of the random variable, often in the form of the Gaussian distribution. The assumption may be, however, difficult to be met in algorithms involving non-linear transformation... View full abstract»

• ### Sparse representation via optimal matching convolution framelets

Publication Year: 2018, Page(s):1082 - 1090
| | PDF (1742 KB)

Recently, a tight frame, called convolution framelets (CFs) and constructed by convolving local and non-local bases, is proposed to provide valuable insights in understanding the patch-based processing approaches in the viewpoint of sparse representation (SR). However, it is still unclear how to represent signals with energy concentration guarantee in its lifted space and how to optimise the local... View full abstract»

• ### Sparse signal recovery via minimax-concave penalty and$\ell _1$ℓ1-norm loss function

Publication Year: 2018, Page(s):1091 - 1098
| | PDF (3112 KB)

In sparse signal recovery, to overcome the ℓ1-norm sparse regularisation's disadvantages tendency of uniformly penalise the signal amplitude and underestimate the high-amplitude components, a new algorithm based on a non-convex minimax-concave penalty is proposed, which can approximate theℓ0-norm more accurately. Moreover, the authors employ the ℓ1-norm loss functi... View full abstract»

• ### Homotopy optimisation based NMF for audio source separation

Publication Year: 2018, Page(s):1099 - 1106
| | PDF (2260 KB)

In this study, the authors propose a novel framework for audio source separation based on a cascaded non-negative matrix factorisation (NMF) using homotopy optimisation with perturbation and ensemble (HOPE) and denoising autoencoder. NMF using traditional optimisation has a problem of finding a global solution, and hence could not achieve complete separation of the sources from the mixture. This p... View full abstract»

• ### Design of nearly linear-phase double notch digital filters with close notch frequencies

Publication Year: 2018, Page(s):1107 - 1114
| | PDF (2981 KB)

In this study, the authors present a new procedure for the synthesis of the nearly linear-phase infinite impulse response (IIR) filters with two close notch frequencies based on all-pass filter application. The filter is obtained using a parallel connection of the delay line and IIR all-pass filter with a piecewise approximately linear phase. The desired magnitude characteristic is achieved by equ... View full abstract»

• ### Blind signal separation method and relationship between source separation and source localisation in the TF plane

Publication Year: 2018, Page(s):1115 - 1122
| | PDF (3504 KB)

A method for solving the instantaneous mixtures of the multiple non-stationary wideband signals in the time-frequency (TF) plane is proposed. The blind source separation is performed by calculation of spatial TF distribution matrices, estimation of a separating matrix, estimation of permutation matrices and scaling matrices and TF synthesis. The simulation result shows that the proposed method imp... View full abstract»

• ### Mixing matrix estimation in UBSS based on homogeneous polynomials

Publication Year: 2018, Page(s):1123 - 1130
| | PDF (1920 KB)

An algorithm is proposed for mixing matrix estimation in underdetermined blind source separation (UBSS) based on homogeneous polynomials representation, in order to blindly identify a mixing matrix in the case where the source signal is insufficiently sparse. First, the observed signal subspaces (hyperplanes) are identified by polynomial fitting, differentiation, and spectral clustering. Then, the... View full abstract»

• ### Two novel sensor control schemes for multi-target tracking via delta generalised labelled multi-Bernoulli filtering

Publication Year: 2018, Page(s):1131 - 1139
| | PDF (2408 KB)

The study addresses the sensor control problem for multi-target tracking via delta generalised labelled multi-Bernoulli (δ-GLMB) filter, and proposes two novel single-sensor control schemes. One is that the Rényi divergence is used as the objective function to measure the information gain between the predicted and posterior densities of the δ-GLMB filter, and it is superior for the overall perform... View full abstract»

• ### Parameter estimation of 2D polynomial phase signals using NU sampling and 2D CPF

Publication Year: 2018, Page(s):1140 - 1145
| | PDF (1985 KB)

The two-dimensional (2D) cubic phase function (CPF) is known as a highly accurate 2D polynomial phase signal estimator, but it has limited applicability due to the requirement for the 3D search for second-order partial phase derivatives. The authors propose an interpolation-based approach simulating non-uniform (NU) signal sampling in order to reduce the 2D CPF calculation complexity. The NU resam... View full abstract»

• ### Adaptive regularisation for normalised subband adaptive filter: mean-square performance analysis approach

Publication Year: 2018, Page(s):1146 - 1153
| | PDF (5238 KB)

The normalised subband adaptive filter (NSAF) is a useful adaptive filter, which improves the convergence rate compared with the normalised least mean-square algorithm. Most analytical results of the NSAF set the regularisation parameter set to zero or present only steady-state mean-square error performance of the regularised NSAF (ε-NSAF). This study presents a mean-square performance analysis of... View full abstract»

• ### Personal verificationbased on multi-spectral finger texture lighting images

Publication Year: 2018, Page(s):1154 - 1164
| | PDF (5515 KB)

Finger texture (FT) images acquired from different spectral lighting sensors reveal various features. This inspires the idea of establishing a recognition model between FT features collected using two different spectral lighting forms to provide high recognition performance. This can be implemented by establishing an efficient feature extraction and effective classifier, which can be applied to di... View full abstract»

• ### Electrocardiogram signal denoising by clustering and soft thresholding

Publication Year: 2018, Page(s):1165 - 1171
| | PDF (1097 KB)

Separating signal from unwanted noise is a major problem when analysing biomedical data, such as electrocardiography. Electrocardiogram (ECG) data are typically a mixture of real signal and various sources of noise, including baseline wander, power line interference, and electromagnetic interference. Since ECG signals are non-stationary physiological signals, the wavelet transform has been propose... View full abstract»

• ### Automated QRS complex detection using MFO-based DFOD

Publication Year: 2018, Page(s):1172 - 1184
| | PDF (4161 KB)

This study proposes a heuristic approach for designing highly efficient, infinite impulse response (IIR) type Digital First-Order Differentiator (DFOD) by employing a nature-inspired evolutionary algorithm called Moth-Flame Optimisation (MFO) for the detection of the QRS complexes in the electrocardiogram (ECG) signal. The designed DFOD is used in the pre-processing stage of the proposed QRS compl... View full abstract»

• ### Hybrid Hughes-Hartogs power allocation algorithms for OFDMA systems

Publication Year: 2018, Page(s):1185 - 1192
| | PDF (3432 KB)

This work analyses the discrete solution of Hughes-Hartogs (HH) for the transmission rate maximisation problem with power constraint in the orthogonal frequency division multiplexing access (OFDMA) systems and explores mechanisms to reduce the computational complexity of greedy algorithms. In addition to the solution characterisation, a computational complexity analysis is developed, considering t... View full abstract»

• ### Mainlobe interference suppression based on independent component analysis in passive bistatic radar

Publication Year: 2018, Page(s):1193 - 1201
| | PDF (5115 KB)

The mainlobe interference is a noticeable issue in the passive bistatic radar (PBR). Because the direction of arrival of interference is close to the target echo, the mainlobe interference can hardly be suppressed effectively by the conventional method. The mainlobe interference will mask the low-level targets of interest, and the blind area of detection will be formed in the direction of the inte... View full abstract»

## Aims & Scope

IET Signal Processing publishes novel contributions in signal processing.

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