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In this paper, we propose a new approach to estimate the low-frequency oscillatory modes in power system by using Total Least Square-Estimation of Signal Parameters employing rotational invariance technique (TLS-ESPRIT) based on Least Mean Squares Sign-Data (LMSSD) Adaptive filtering. LMSSD adaptive filtering reduces the effect of Additive White Gaussian Noise (AWGN) from the signal. The proposed...
This paper deals with the results on the reconstruction accuracy of the irregularly sampled discrete-time signal (DTS) with unknown sampling locations. Reconstruction is performed by means of special reconstruction algorithms based on the sampling locations estimation. Comparison is done for results of estimation of the algorithms accuracy and accuracy of signal reconstruction by means of interpolation...
This paper proposes a Doppler estimation algorithm for underwater acoustic communication by constructing the guide function of the objective function based on linear frequency modulation (LFM) signal. The algorithm employs the least square principle and the particle swarm method, to build the objective function and solves the global optimal solution, respectively. Computer simulations show that the...
In this paper the dynamic compressed sensing (DCS) estimation of time varying underwater acoustic (UWA) channel is investigated. By modeling the time varying UWA channels as sparse set consisting with constant and time-varying supports, the estimation of time varying UWA channel is transformed into a problem of dynamic compressed sensing (DCS) sparse recovery. Employing the combination of Kalman filter...
This paper proposes a novel hybrid position estimation strategy based on merging two self-sensing techniques according to the operating speed. High-frequency (HF) signal injection algorithm is deployed for zero and low-speeds, while the Machine Learning (ML) method is adopted for medium and high speeds. The proposed position estimator is intended for the fault-tolerant control of an interior permanent-magnet-synchronous...
Automatic Modulation classification lays important role in the systems of electromagnetic spectrum monitoring. However performance of the algorithms is depreciated due to inaccurate estimation of signal parameters. The problem of unknown parameters is well documented in the literature however, authors usually propose improved algorithms in order to maximize probability of correct classification when...
The popularly used current controlled architecture for grid connected converter systems needs a phase locked loop (PLL) for its operation. The PLL generates the unit vectors required for desired current reference generation. This paper proposes to eliminate the grid voltage sensor and presents a method to estimate the unit vectors and grid frequency without a dedicated grid voltage sensor. The estimation...
This paper proposes a novel frequency-based predictive sequence extractor that allows to isolate the harmonic components of both voltages and currents needed for the control of grid-tied converters. The proposed method is based on a modification of the Sliding Goertzel Transformation (SGT) that allows to include a predictive behavior with a prediction horizon equal to the processing window needed...
This paper proposes a blind interleaver period estimation algorithm by sorting error-less symbols. After finding the error-less symbols through the rank distribution of the square matrices, we construct a rectangular matrix by locating errorless symbols on the top of a matrix. By analyzing this matrix, we can estimate the interleaver period. Experimental results show that the proposed algorithm has...
State-of-the-art sensing methods only exploit three dimensions of the spectrum space: frequency, time and geography whereas the angle dimension, that is, spatial spectrum sensing has not been exploited well enough. In this paper, we apply the multiple signal classification (MUSIC) Angle of Arrival (AoA) estimation method into spectrum sensing. Note that MUSIC method needs to know the number of signals,...
Parameters estimation is a crucial and challenging component for Frequency-Hopping (FH) communication. Time-frequency analysis is a valid signal processing tool to estimate parameters of FH signal. However, the existing Time-Frequency analysis methods have several shortcomings such as weak suppression noise interference and feeble concentration of Time-Frequency, resulting in inaccurate parameter...
This paper studies the networked estimation of the state of a linear dynamical system. The focus is on developing a distributed estimation algorithm which could achieve the same performance as the centralized ones. A communication protocol which formally describes the network topology is introduced. By performing this protocol, the sum of the information vector contributions is computed, which is...
Automatic estimation of symbol parameters plays a prominent role in electronic reconnaissance and electronic warfare systems. How to estimate the code width without prior knowledge is an important problem in modulation recognition. Hilbert transform can effectively extract the instantaneous mutation characteristics of digital communication signals. In this paper, in order to demodulate MPSK underwater...
In wireless sensor networks (WSNs), each sensor node can estimate the global parameter from the local data in a distributed manner. This paper proposed a diffusion estimation algorithm based on sub-regions, which are referred to as the SR-DLMS algorithm. The proposed algorithm divides the sensor network into several sub-regions, which used to estimate sub-dimensions of the parameter. Compared with...
Direction of arrival (DoA) estimation in the massive antenna systems with reduced hardware and signal processing complexity is a challenging task. To address the issue, this paper presents an approach to estimate the DoA in a large number of antennas system combined with an electromagnetic (EM) lens. An EM lens has the ability to focus the received signal energy as a function of the angle of arrival...
We propose a likelihood test for a covariance estimated from sample data which is used to determine the number of narrow band source signals. This Minimum Description Length (MDL) estimator is shown to be robust against deviations from the assumption of equal noise level across the array. A number of source Direction-Of-Arrivals (DOA) greater than the number of physical array elements is of interest...
In this paper, we consider the problem of direction-of-arrival (DoA) estimation using electronically steerable parasitic array radiator (ESPAR) antenna based on compressive sensing. For an ESPAR antenna, the beampatterns and sparse model of DoA estimation problem in terms of overcomplete dictionary and sampling grid is presented. The DoA estimation problem is formulated as a mixed-norm ℓ2,1 minimization...
Most of multichannel sound source Direction Of Arrival (DOA) estimation algorithms suffer from spatial aliasing problems. The Interchannel Phase Differences (IPDs) are wrapped beyond the spatial aliasing frequency. This invalidates the DOA estimation due to significant errors. A real-time algorithm is proposed to address the general IPD wrapping problem for both single-source and multi-source scenarios...
The problem of computing the Fourier Transform of a signal whose spectrum is dominated by a small number k of frequencies quickly and using a small number of samples of the signal in time domain (the Sparse FFT problem) has received significant attention recently. It is known how to approximately compute the k-sparse Fourier transform in \approx k\log^2 n time [Hassanieh et alSTOC12], or using the...
This report discusses the implementation of a computerized algorithm specifically designed to measure the syllables-per-minute rate of abnormal speech typically produced by persons suffering from an articulatory disorder known as dysarthria. This speech rate measurement application — which can also serve as a diagnostic tool in itself — has been integrated into the computerised Frenchay Dysarthria...
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