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Canonical polyadic decomposition (CPD), also known as PARAFAC, is a representation of a given tensor as a sum of rank-one tensors. Traditional method for accomplishing CPD is the alternating least squares (ALS) algorithm. This algorithm is easy to implement with very low computational complexity per iteration. A disadvantage is that in difficult scenarios, where factor matrices in the decomposition...
This paper presents a novel real-valued multiple signal classification (RV-MUSIC) algorithm, which tremendously reduces the computation complexity than the complex one by a factor of four. The covariance matrix of the sensor output is firstly transformed into a real-valued covariance matrix via unitary forward/backward (FB) technique. Then the MUSIC algorithm in real domain is used to estimate the...
Massive MIMO transmission has been attracted much attention as one of key technologies in next-generation mobile communication system, because it enables improvement in service area and interference mitigation by simple signal processing. Multi-beam massive MIMO configuration has proposed that utilizes the beam selection with high power in analog part and blind algorithm such as constant modulus algorithm...
A modified TS-ESPRIT algorithm estimates direction of arrival (DOAE) for target and increases the estimation accuracy is introduced. This algorithm divides the planar array into a multiple uniform sub-planar arrays with common reference point and then the temporal subspace approach in ESPRIT method (T-ESPRIT) is applied for each sub-array. Moreover, the proposed algorithm is combined the T-ESPRIT...
the complexity of sphere detection algorithm is high when the Signal to Noise Ratio (SNR) is low. For this problem, a new type of detection algorithm of sphere decoder is proposed. The new algorithm reduces the radius of sphere when the SNR is low by using the Minimum Mean Square Error (MMSE) algorithm and a compressibility factor. With the result of simulation, It shows that when the SNR is less...
In this paper various adaptive filters have been thoroughly applied to biomedical data processing in the aim to implement a barrier between noise reduction and preservation of the useful information. Electrocardiography (ECG) presents one of the most important indicators, which can be informed of the recognizing approaches to discover heart disease. Due to its inherent importance, it is interesting...
The methods of dynamic access to spectrum developed in Cognitive Radio require efficient and robust spectrum detectors. Most of these detectors suffer from four main limits: the computational cost required for the detection procedure; the need of prior knowledge of Primary User's (PU) signal features; the poor performances obtained in low SNR (Signal to Noise Ratio) environment; finding an optimal...
Computational auditory scene analysis (CASA) system is well used in speech enhancement area in recent years. We propose a new system that combines CASA and spectral subtraction to get better enhanced speech. The CASA part consists of the latest method deep neural networks (DNNs). The original way to reconstruct the denoise signal is to use the estimated masks with direct overlap-add method ignoring...
We consider the robust PCA problem of recovering a low-rank matrix corrupted by Gaussian noise and large elementlevel outliers. Motivated by the sparse estimation literature, we consider outlier rejection schemes that apply hard or soft thresholding, respectively, to the elements of the data matrix to efficiently estimate the sparse component and then apply an SVD on the residual matrix to estimate...
In this paper, we address the preparation of ecological datasets for data mining. We propose a new adaptive method for automatic dataset construction using Erblet transform, which can be seen as a non-uniform filter bank where the center frequency and the bandwidth of each filter match the ERB (Equivalent Rectangular Bandwidth) scale, followed by data quality assessment using a tonality index (TI)...
Millimeter-wave (mm-Wave) systems with $\mbox{hybrid digital-to-analog beamforming (D-A BF)}$ have the potential to fulfill 5G traffic demands. The capacity of mm-Wave systems is severely limited as each radio frequency (RF) transceiver chain in current base station (BS) architectures support only a particular user. In order to overcome this problem when high density of users are present, a new algorithm...
In this paper, we propose an adaptive filtering algorithm, Hybrid Recursive and Least Mean Square-based Constant Modulus Algorithm (RLS-LMS-CMA) for optimized blind beamforming for a Uniform Linear Array (ULA). We consider that Recursive Least Square-based Constant Modulus Algorithm (RLS-CMA) and Least Mean Square-based Constant Modulus Algorithm (LMS-CMA) algorithms are time tested. Therefore, we...
Robust adaptive beamforming (RAB) has became a popular research topic, with various RAB techniques being proposed in the past decades. However, because the sample covariance matrix rather than the interference-plus-noise co-variance matrix is used to calculate the weight vector, the performance of the previously developed RAB techniques is not optimal. In this paper, a novel RAB algorithm, which uses...
The truncated version of the higher-order singular value decomposition (HOSVD) has a great significance in multi-dimensional tensor-based signal processing. It allows to extract the principal components from noisy observations in order to find a low-rank approximation of the multi-dimensional data. In this paper, we address the question of how good the approximation is by analytically quantifying...
The cognitive radio is considered a best solution for the limited spectrum resources problem. The periodogram based energy detection can be used for spectrum estimation in cognitive radio. It does not need any prior information about the primary signal. This paper presents a new periodogram by using the Discrete Cosine Transform (DCT). In addition, it analyses and compares the performance with raw...
This article presents a Bayesian track-before-detect (TBD) method based on Gaussian message passing to detect and track a target in the low SNR scene. Removing the threshold brings great computation demanding to TBD methods. Because of the distributive law and computation consistency, message passing can reduce the calculation load efficiently. Also, as a probabilistic inference algorithm, message...
A new parameters estimation approach for mixed sources is proposed in this paper, which is under the sparse signal reconstruction framework. By reconstructing of covariance matrix, directions of arrival (DOAs) in the far-field part were estimated with an l1-svd-like method directly. Then the subspace difference method was adopted to obtain the near-field covariance matrix, and the relative DOAs can...
This paper is devoted to development of nonlinear filter of Markov processes for JPEG images at the stage of preprocessing, allowing to increase the filtration quality when off-line and on-line image recovering. The analysis of wide interference class affecting the image is held. The proper processing algorithm is developed for each kind of noise. Evaluating the synthesized algorithm effectiveness...
A possible variant of the signal processing for detection of weak pulsar signals is presented in this paper. The signal processing incudes three basic stages: epoch folding, moving average filter with a jumping window and adaptive signal detection. The signal processing proposed in the paper was verified with real experimental signal records from pulsar B0329+54 by the Westerbork Synthesis Radio Telescope...
Beamforming (BF) protocols introduced in IEEE 802.11ad and IEEE 802.15.3c for 60 GHz millimeter-wave (mmwave) communications perform exhaustive sector/beam search to setup a beamformed link between stations/devices. In this paper, we propose two BF methods, Binary Search Beamforming (BSB) and Linear Search Beamforming (LSB), to improve the BF setup time of adopted algorithms in IEEE 802.11ad and IEEE...
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