Frequency-estimation algorithms devised for complex sinusoids, including the maximumlikelihood (ML) approach, when operating on real sinusoidal signals, suffer from spectral interference due to the superposition of the aliasing components at negative and positive frequencies. This paper introduces a frequency estimation ML-like algorithm, based on a spectral-matching approach, that avoids such ...

In statistics parameter theory, usually the parameter estimations have two kinds,one is the least-square estimation(LSE),and the other is the best linear unbiased estimation (BLUE).Due to the determining theorem of minimum variance unbiased estimator(MVUE),the parameter estimation of BLUE in linear model is most ideal.But since the calculations are complicated or the covariance is not given,peo...

Accurate estimation of the parameters of an elliptical shape is required in various machine-vision and computer-vision problems. In our previous work, we have addressed this problem by proposing to optimize a weighted minimum-squares-error (MSE) function. As a continuation of this work, we have studied other techniques for elliptical-parameter estimation, ones applying elliptical-Fourier descri...

This paper presents a Modified ILSE technique for global motion estimation where Gradient Thresholding (GT) is used to analyze and preprocess the image blocks before motion estimation. By means of GT, treacherous blocks that are more likely to produce inaccurate motion estimations are identified at the beginning and discarded from the following process. So, the computational cost is reduced to ...

In this paper a new technique for performing image registration to subpixel accuracy is presented. The proposed technique, which is based on the maximization of the correlation coefficient, does not require the reconstruction of the intensity values and provides a closed-form solution to the subpixel translation estimation problem. Moreover, an efficient iterative scheme is proposed, which redu...

1 In linear regression with fixed design, we propose two procedures that aggregate a datadriven collection of supports. The collection is a subset of the 2 possible supports and both its cardinality and its elements can depend on the data. The procedures satisfy oracle inequalities with no assumption on the design matrix. Then we use these procedures to aggregate the supports that appear on the...

This paper proposes a novel method for early termination of a motion search. It first introduces an estimator of the sum of absolute difference (SAD) between the current block and a search point. After analyzing the SAD estimator, it proposes the SAD condition to decide whether the current search point is around a minimum point or not. The counter condition is used to evaluate the current searc...

Motion compensation using the optimal full search algorithm is often too computational heavy for real time implementation. Many suboptimal fast search algorithms have been proposed. In particular, Liu and Zaccarin proposed the Alternating Subsampling Search Algorithm (ASSA). The ASSA reduces the computation by subsampling the pixels instead of limiting the search locations. It was shown that AS...

State-space models offer a powerful modelling tool for time series prediction. However, as most algorithms are not optimized for longterm prediction, it may be hard to achieve good prediction results. In this paper, we investigate Gaussian linear regression filters for parameter estimation in state-space models and we propose new long-term prediction strategies. Experiments using the EM-algorit...

Typical Double Auction (DA) models assume that trading agents are one-way traders. With this limitation, they cannot directly reflect the fact individual traders in financial markets (the most popular application of double auction) choose their trading directions dynamically. To address this issue, we introduce the Bi-directional Double Auction (BDA) market which is populated by two-way traders...