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This paper concerns the problem of calculating expectation shift due to variability which tends to occur whenever the function of a random variable is nonlinear and especially tends to occur in the neighborhood of a local maximum or minimum. The paper presents five theorems suggesting sampling points and formulae for estimating mean shift covering some of the most common cases of practical interest...
In this paper we propose a robust energy detector for spectrum sensing in cognitive radio systems. The detector is derived by modelling the noise process as consisting of two components, Gaussian noise and impulsive noise. The impulsive noise is modelled using a uniform distribution that appears with a certain probability. A convenient approximation using the max operator is then applied to the resulting...
Structural scan based delay testing is used to detect delay faults. Because of the architectural limitations not each test pair v1, v2 can be applied by scan delay testing. That declines test coverage. Partial enhanced scan approach based on selection of flip-flops was suggested to permit using arbitrary test pairs v1, v2. The problem of selection of flip-flops may be solved with applying estimations...
This paper introduces the covariance matrix of visually salient image features as a compact and robust descriptor for near duplicate image and video copy detection. We make two novel contributions. We first present a fast method for computing information theoretic based visual saliency maps using a data independent fast transform to replace the conventional data dependent computationally demanding...
We present a new approach to estimate the focal length for camera calibration in multiview reconstruction. As a popular camera calibration approach, minimal solution method gives rise to a great number of focal-length estimates, from which generating an accurate one is of great significance. Our method concentrates on how to obtain an accurate estimate and is carried out in two steps: firstly, a norm...
In this paper, a robust QAM classification in a frequency offset channel is considered. When a carrier frequency is not recovered with the sufficient accuracy in a receiver, a signal point rotates in a vector diagram. This paper presents the classification method by the amplitude and squared cosine moments. In the method, phase shifts are employed for the squared cosine moments in order to change...
Many tracking algorithms have difficulties dealing with occlusions and background clutters, and consequently don't converge to an appropriate solution. Tracking based on the mean shift algorithm has shown robust performance in many circumstances but still fails e.g. when encountering dramatic intensity or colour changes in a pre-defined neighbour hood. In this paper, we present a robust tracking algorithm...
Considering noise interference often exists in audio processing, it is not robust enough to calculate audio similarity by using distance measure directly. In this paper, basing on Renyi's quadratic entropy, a novel scheme for audio similarity measure is proposed. In our work, we extract Mel Frequency Cepstral Coefficients (MFCCs) to represent each audio, and then calculate the similarity based on...
Robust Parameter Design (RPD) is one of the key approaches to improve product quality. The paper proposes an RPD approach for optimizing processes with multiextreme quality characteristics. Firstly, support vector regression (SVR) is selected as the basic fitting model for a concerned process. Secondly, uniform space filling design is used to arrange the levels of control factors and noise factors,...
In this paper, we propose a new two-stage Rao test detector, which is obtained by cascading a subspace detector (SD) and the Rao test. A set of secondary data is available and noise returns in primary and secondary data share the same statistical characterization. Analytical expressions for the probability of false alarm (Pfa) and the probability of detection (Pd) are provided in homogeneous environment...
A novel video motion object automatic segmentation algorithm based on Gaussian Markov random field is studied in this paper. In this algorithm, the probability density functions of the different images are estimated as Gaussian mixture distributions, moving object detection algorithm based on integrating maximizer of the posterior marginals with MAP. Firstly, initial segmentation is applied to obtain...
Decomposition of cells in clumps is a difficult segmentation task requiring region splitting techniques. Techniques that do not employ prior shape constraints usually fail to achieve accurate segmentation. Those using shape constraints are unable to cope with large clumps and occlusions. In this work, we propose a model-constrained region splitting algorithm for cell clump decomposition. We build...
Modeling with a small set of samples will normally result in great variance. This research proposes a unique procedure for small sample regression systematically using the concept of robust Bayesian inference and a contamination prior. The approach enlarges the possible domain of population information and attempts to estimate regression parameters. A data augmentation step included in the procedure...
Performance of communications systems receivers is generally estimated by the bit error rate (BER) which is computed using the Monte Carlo (MC) simulation (Bit Error Counting). In a previous paper, an alternative new method based on an estimation in an iterative and nonparametric way, of the probability density function (pdf) of the soft decision of the received bit, was suggested. It was shown that...
In many practical situations, we have several estimates x1, ..., xn of the same quantity x, i.e., estimates for which x1 ≈ x, x2 ≈ x, ..., and xn ≈ x. It is desirable to combine (fuse) these estimates into a single estimate for x. From the fuzzy viewpoint, a natural way to combine these estimates is: (1) to describe, for each x and for each i, the degree μ≈(xi-x) to which x is close to xi, (2) to...
This paper proposes an experimental analysis focusing on the sensitivity of three behavioral models, Memory Polynomial (MP), Augmented Hammerstein (AH) and the two hidden layers artificial neural networks (2HLANN) to the characteristics of the input signal driving the power amplifier (PA) to be linearized. The analysis is carried out by changing separately each signal characteristic, respectively...
Many measurement applications, in particular for biological, biomedical and biochemical systems, deals with the problem that only short data records are available. This problem implies that many powerful statistical tools are not applicable since these tools are based on asymptotic results. No user-friendly guidelines are available when dealing which such sparse datasets.In contrast to an estimator,...
In this paper, a fundamental but important statistical signal processing characteristic, namely the Gaussianity or normality, is studied. In contrast to the existing conventional Gaussianity measures, we propose a novelmeasure, which is based on Kullback-Leibler divergence (KLD) between the Gaussian probability density function (PDF) and the generalized Gaussian PDF incorporated with the skewness...
This paper proposes a robust detector for detection of known signals in impulsive noise environments. The distribution of the noise is assumed to be a mixture of Laplacian distribution giving a sharp peak around the true value of the signal of interest and uniform distribution modeling the contributions of completely unknown noise. This type of noise appears in problems related to estimated pitch...
The nonlinear robust stability theory of Georgiou and Smith (IEEE Trans. Auto. Control, 42(9):1200-1229, 1997) is generalized to the case of notions of stability with bias terms. An example from adaptive control illustrates non trivial robust stability certificates for systems which the previous unbiased theory could not establish a non-zero robust stability margin. This treatment also shows that...
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