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In room acoustics, the under-modelled blind system identification (BSI) problem arises when the identified room impulse response (RIR) is shorter than the real one. Conventional BSI methods can perform poorly under these circumstances. In this paper, we propose an algorithm for multichannel BSI in under-modelled situations. Instead of minimizing the cross-relation error, a new optimization criterion...
We investigate the problem of finding the real-valued vectors h, of size L, and x, of size P, from M independent measurements ym = 〈am, h〉〈bm, x〉, where am and bm are known random vectors. Recovery of the unknowns entails solving a set of bilinear equations, a challenging problem encountered in signal processing tasks such as blind deconvolution for channel equalization or image deblurring. Inspired...
This paper presents a new Bayesian strategy for the estimation of smooth signals corrupted by Gaussian noise. The method assumes a smooth evolution of a succession of continuous signals that can have a numerical or an analytical expression with respect to some parameters. The Bayesian model proposed takes into account the Gaussian properties of the noise and the smooth evolution of the successive...
In this paper we propose an extension of a blind source separation algorithm that can be used to process the data obtained by an array of ion-selective electrodes to measure the ionic activity of different ions in an aqueous solution. While a previous algorithm used a polynomial approximation of the mixing model and mutual information as means of estimating the mixture coefficients, it only worked...
The metric in the reproducing kernel Hilbert space (RKHS) is known to be given by the Gram matrix (which is also called the kernel matrix). It has been reported that the metric leads to a decorrelation of the kernelized input vector because its autocorrelation matrix can be approximated by the (down scaled) squared Gram matrix subject to some condition. In this paper, we derive a better metric (a...
In diagnosis and treatment planning of brain tumors, characterisation and localization of tissue plays an important role. Blind source separation techniques are generally employed to extract the tissue-specific profiles and its corresponding distribution from the multi-parametric MRI. A 3-dimensional tensor is constructed from in-vivo multi-parametric MRI of high grade glioma patients. Constrained...
Image denoising is a fundamental problem in image processing and many powerful algorithms have been developed. However, they often rely on the knowledge of the noise distribution and its parameters. We propose a fully blind denoising method that first estimates the noise level function then uses this estimation for automatic denoising. First we perform the nonparametric detection of homogeneous image...
In this paper some results on Schur transform are reviewed to address the problem of one-dimensional discrete phase retrieval. The goal is to provide a test whether a sequence of input magnitude data gives a solution to one-dimensional discrete phase retrieval problem. It has been previously shown that this issue is related to the nonnegativity of trigonometric polynomials. The proposed method is...
The problem of cyclic spectrum estimation for almost-cyclostationary processes with unknown cycle frequencies is addressed. This problem arises in spectrum sensing and source location algorithms in the presence of relative motion between transmitter and receiver. Sufficient conditions on the process and the cycle frequency estimator are derived such that frequency-smoothed cyclic periodograms with...
Tracking of low SNR signals is challenging task. The algorithm for tracking of single object observed as line in single image is proposed in this paper. The object signal signature is periodic with unknown pattern. Proposed algorithm uses multidimensional scatter with variable parameters for exhaustive search of solution. Example results are provided for the simplified 1D case using Monte Carlo approach.
The length of Beidou CB2I code is twice that of the Global Position System (GPS) C/A code, and the resource consumption will be doubled on embedded hardware with a finite resource if it is processed with the traditional algorithm. Hence, this paper proposes an acquisition algorithm based on combined Fast Fourier Transform (FFT), which separates a signal into odd and even sequences and processes them...
Visual target tracking is one of fundamental research of computer vision field and play an important role in the surveillance application, but it is also one of the difficulties due to the instability of the tracking scene. In this paper, we analyze the major drawbacks of the original Kernelized Correlation Filter (KCF) tracker which causes tracking failure when target experience complicated scenarios...
This paper introduces a subspace method for the estimation of an array covariance matrix. When the received signals are uncorrelated, it is shown that the array covariance matrices lie in a special subspace defined through all possible correlation vectors of the received signals and whose dimension is typically much smaller than the ambient dimension. Based on this observation, a subspace-based covariance...
Synthetic Aperture Radar (SAR) imaging can suffer distortion in the presence of phase errors in the acquired signal data caused by the non-ideal platform motion trajectory. Autofocus algorithms are used to remove the undesired phase error through signal processing techniques. Multi-channel convolution model of the SAR autofocus problem is established on the condition that phase error is range-independent...
This paper deals with implementing a real-time gunshot detection algorithm on the digital signal processor TMS320C6713. The developed algorithm uses 3 linear predictive coding coefficients, energy in 3 spectral bands, and frame correlation. The audio input signal is continuously processed and signal frames considered to contain a gunshot are shortly signalized by an LED indicator. Experimental results...
This work aims at implementing an asynchronous FIR adaptive filter, based on the Recursive Inverse (RI) adaptive algorithm. Previous work has presented the proposed adaptive filter algorithm and has shown that the algorithm's performance is similar to that of the Recursive Least Squares (RLS) algorithm. Moreover, it offers better performance than the Transform Domain (TD) algorithms, i.e. the TD LMS...
Satellite signal acquisition is indispensable for signal tracking and solution, and its operating time directly determines the starting speed of the software receiver. The length of Beidou code is twice of Global Positioning System (GPS) C/A code. Therefore, the acquisition time will increase with the traditional algorithm. This paper proposed a fast acquisition algorithm which decomposed the N points...
The method of detection and identification of a low Doppler target under conditions of intensive disturbances having fluctuating character is investigated in this article. The proposed algorithm for calculating the estimations of the target spatial position and the Doppler frequency translation of a signal reflected from the target is an optimum from the standpoint of the maximum of likelihood. The...
This article describes methods to reduce the computational complexity of signal processing algorithms in passive radar systems using signals of opportunity. Review of existing algorithms is produced. Signal processing algorithms for passive radar systems, which reduces the computational cost are developed. Noise influence to the proposed algorithm is investigated.
In this paper, demodulation method by using adaptive filter with initial condition is proposed. In the proposed method, message signal is recovered from amplitude and phase of reference carrier signal. The initial weights for adaptive filter are determined by representing the adapted weight equation in the form of the difference equation. The results obtained from both computer and TMS320C6713 digital...
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