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Tracking the direction of arrival (DOA) of an acoustic source in an impulsive noise environment is a challenging problem due to the non-Gaussian characteristic of the noise process. In this paper, a particle filtering (PF) with fractional lower order moment (FLOM) likelihood model is developed to solve this problem. A constant velocity model is employed to model source dynamics and alpha-stable processes...
In the seesaw (or cyclic or alternating) method for optimization and identification, the full parameter vector is divided into two or more subvectors and the process proceeds by sequentially optimizing each of the subvectors while holding the remaining parameters at their most recent values. One advantage of the scheme is the preservation of large investments in software while allowing for an extension...
Mean Value Engine Models (MVEM) are used to model the averaged dynamics of an automobile engine system for control and fault diagnosis. One approach to automobile fault diagnosis is to employ the use of a bank of residual generators each of which use a fault model and produces fault residues. These fault residues could then be used to detect or isolate faults using fault detection logic in the Fault...
Mean Value Engine Models (MVEM) have been used to model the averaged dynamics of an automobile engine system for automotive control and fault diagnosis. For these purposes, it is common to estimate states of interest given noisy measurements using state observers. Since the measurements could be noisy and asynchronous, they should be suitably post-processed before feeding them to a state observer...
This paper proposes an adaptive fuzzy logic control (FLC) for the speed control of the permanent magnet synchronous motors (PMSM). The mean and the variance of the Gaussian membership function are updated in real time, until convergence of the error is achieved. The weights used for combining the fuzzy rules are also updated, using the least mean square algorithm. The paper also demonstrates a robust...
A good investment strategy requires a combination of mathematical modeling with deep understanding of the economics of the market. The basis of the portfolio optimization is the mean-variance optimization put forwarded by Markowitz in 1952. The optimization procedure depends on the input parameters, the covariance matrix and expected return which have to be estimated using the historical data. The...
Recently the kernel discriminant analysis (KDA) has been successfully applied in many applications. KDA is one of the nonlinear extensions of Linear Discriminant Analysis (LDA). But the kernel function is usually defined a priori and it is not known what the optimum kernel function for nonlinear discriminant analysis is.
Multiple-input multiple-output (MIMO) channel is often triply selective, meaning that it has spatial, temporal and inter-tap correlation. The temporal correlation is well characterized by its Doppler spectrum, but spatial and inter-tap correlation and their impact on MIMO channels are less studied in the literature. A MIMO testbed has been established to measure the impulse response of MIMO channels...
For calibration of general radially symmetric distortion of omnidirectional cameras such as fish-eye lenses, calibration parameters are usually estimated so that curved lines, which are supposed to be straight in the real-world, are mapped to straight lines in the calibrated image, which is called plumbline principle. Under the principle, the camera with radially symmetric distortion can be calibrated...
While wireless sensor network aided robots lend humans a hand in accessing to certain difficult and/or otherwise unreachable areas, the robots may face challenges in locomotion, object discovering, searching and tracking among many demanding tasks. The unreliable wireless communication and possible components failures of wireless sensor nodes coupling with the noises in the uncertain environments...
In this paper, clutter suppression and target detection in clutter edge is discussed. Firstly the statistical model of the clutter edge is established, based on which maximum likelihood estimation for the transition range bin of the clutter edge is derived. Simulations illustrate that by carefully choosing the secondary samples based on the estimation result of the transition range bin, the signal...
A fast direction of arrival (DOA) estimation method is presented in this paper for monostatic multiple-input multiple-output (MIMO) radar with arbitrary array configuration. In order to avoid spectral peaks search in the multiple signal classification (MUSIC) algorithm and reduce the computational complexity, the proposed method uses manifold separation and polynomial rooting technique to estimate...
Recently, several robust covariance matrix estimation techniques were proposed, such as normalized sample covariance matrix (NSCM) and fixed point matrix (FPM). They were claimed to be able to provide better performance for non-Gaussian clutter or in the presence of disturbance. In this paper, the performance of these robust covariance matrix estimators were evaluated and compared with the conventional...
In this paper we figure out a method which can be used by arrays mounted on moving platforms to detect the fully correlated signals. The algorithm proposed is similar to the spatial smoothing technique proposed by T. J. Shan, but it does not depend on any particular form of the arrays, and can be performed without loss of array aperture. Simulation results are offered to confirm the validity of the...
A robust D-InSAR deformation phase estimation method is proposed. The method can accomplish the images auto-coregistration by using joint processing of multiple pixels and the phase noise suppression by using signal subspace fitting. The performance is investigated using simulated data.
In this paper, a new Direction of Arrival (DOA) estimation method is proposed with uniform linear array when both uncorrelated and coherent sources are present. After denoising the received data by wavelet transform, first the DOAs of uncorrelated signals are estimated using Independent Component Analysis (ICA). Afterwards, the information of uncorrelated signals is eliminated and a new matrix is...
The long term goal of our project is the development of robust Security Speech Recognition systems are based on Automatic Speech Recognition methodologies. The development of ASR systems involves dealing with issues such as Acoustic Phonetic Decoding (APD), Language Modelling (LM) or the development of appropriated Language Resources (LR). Thus these applications are generally very language-dependent...
Estimation of the number of sources embedded in noise is a fundamental problem in statistical signal and array processing. This paper focuses on a non-parametric tool to estimate the number of sources without any information about the signature matrix. We exploit the behavior of eigenvalues of the sample covariance matrix and propose a new estimator based on a sequence of hypothesis test. A series...
In this study, we continue our analysis on the use of RLS in neural fuzzy systems. The recursive least square (RLS) algorithms can have great learning performance for neural fuzzy networks. From our previous work, it can be observed that the advantages of using RLS instead of using BP are not so obvious. For the use of forgetting factor in RLS, the idea is to account for the effects of the change...
In order to tackle more efficiently the parameters estimation of an Output Error (OE) models contaminated by outliers, we propose to extend the range of the scaling factor of a parameterized robust estimation criterion (PREC) in the Huber's M-estimates context based on a mixed norm. Moreover, since the gradient and the Hessian of the PREC present a nonlinear structure in the OE models, we propose...
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