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This paper analyzes the effect of waveform parameters on the joint target location and velocity estimation by non-coherent multiple-input multiple-output (MIMO) radar transmitting multiple subcarriers signals without energy constraint. How the number of subcarriers influence the estimation accuracy is illustrated by considering the joint Cramer-Rao bound (CRB) and the mean square error (MSE) of the...
A distributed EM algorithm with consensus is proposed for density estimation and clustering using WSNs in the presence of mixtures of Gaussians. The EM algorithm is a general framework for maximum likelihood estimation in hidden variable models, usually implemented in a central node with global information of the network. The average consensus algorithm is a simple robust scheme for computing averages...
In this paper, a new method for Bayesian periodic parameter estimation is derived using periodic cost functions. The estimation procedure is evaluated using Fourier series representation of the periodic cost functions. The minimum cyclic and the minimum periodic mean-square-error (MSE) estimators are derived. The proposed periodic estimators are applied to direction-of-arrival (DOA) estimation problem...
Consider estimating the parameters of polynomial phase signals observed by an antenna array given that the array manifold is unknown (e.g., uncalibrated array). To date, only an approximated maximum likelihood estimator (AMLE) was suggested, however, it involves a multidimensional search over the entire coefficient space. Instead, we propose a two-step estimation approach, termed as SEparate-EStimate...
This paper presents a modified prequential Bayes (MPB) method for model order estimation of Gaussian mixture models (GMM). The proposed MPB order estimators recursively update the weighting for each order in a class of model orders from the mixture of a time-invariant prior and the likelihood of the observed data for each model. This paper investigates both a maximum a posteriori (MAP) switching version...
In this paper, we consider the effect of different rules of symbol decision on the performance of decision-directed synchronizers for LDPC-coded systems. Different from the conventional hard symbol decision based on the Maximum-A- Posteriori (MAP) criterion, soft symbol decision can be considered as the Minimum-Mean-Square-Error (MMSE) estimation of the transmitted symbol. By whether or not the coding...
This paper studies the problem of pilot-aided joint carrier frequency offset (CFO) and channel estimation using a Bayesian approach in multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) transmissions over time- and frequency-selective (doubly selective) channels. Unlike the joint CFO and channel impulse response (CIR) estimation over block-fading channels, the...
In this paper, we investigate carrier frequency synchronization in the downlink of 3GPP Long Term Evolution (LTE). A complete carrier frequency offset estimation and compensation scheme based on standardized synchronization signals and reference symbols is presented. The estimation performance in terms of mean square error is derived analytically and compared to simulation results. The impact of estimation...
The development of model-based processing techniques in ocean acoustics is well-known evolving from the pure statistical approach of maximum likelihood parameter estimation, matched-field processing and sequential model-based processing for Gaussian uncertainties. More recent model-based techniques such as unscented Kalman filtering (UKF) and sequential Markov chain Monte Carlo (MCMC) methods using...
We develop iterative turbo receivers for time-variant fading channels which jointly perform channel and frequency offset estimation together with data detection and decoding. Three versions of the joint estimator, the Bayesian, the maximum likelihood and the regularised-maximum likelihood are presented depending on how much knowledge of channel statistics is available. The estimation and detection...
This paper proposes a new method based on the combination of a soft-decision ranging and Maximum A Posteriori (MAP) estimation for Impulse Radio type Ultra Wide Band (UWB-IR) Time of Arrival (TOA) localization. The soft-decision ranging assigns the probability of being generated by a signal to each component in the observed instantaneous power delay profile (the probability density function (pdf)...
The current state-of-the-art in high-rate acoustic communications is represented by adaptive multi-channel equalization of single-carrier wideband signals, which is used in real-time acoustic modems and as a benchmark for coherent communications performance. An alternative technique with significant potential for achieving high bit rates over multipath-distorted (frequency selective) channels is multi-carrier...
Based on the theory of Markov Random Fields, a Bayesian regularization model for diffusion tensor images (DTI) is proposed in this paper. The low-degree parameterization of diffusion tensors in our model makes it less computationally intensive to obtain a maximum a posteriori (MAP) estimation. An approximate solution to the problem is achieved efficiently using hierarchical Markov Chain Monte Carlo...
This paper presents a learning method of a structuring element for morphological image generative model by using a maximum a posterior (MAP) estimation. Mathematical morphology provides set-theoretic image processing methods. In the morphological processing, an image is approximated as a union of translated and level-shifted structuring elements. The specification of the structuring element is crucial...
This paper presents a novel denoising algorithm for color images. It is difficult to reduce color noise at high speed without losing image details. To solve this problem, the proposed method employs maximum a posteriori (MAP) estimation based on a Gaussian model in ε-neighborhood of the pixel and CIELAB color space. Using the correlation between RGB components in ε-neighborhood, color noise is reduced...
In this paper, a dense motion field estimation technique based on the Bayesian framework is proposed to estimate the true dense motion fields of video sequences. Previous stochastic techniques of dense motion field estimation adopts piecewise smooth motion model and use MAP estimation to find the motion field with joint minimization of motion compensation errors and maximization of motion smoothness...
In this paper a novel method for knowledge space construction is proposed. The method is based on the optimization of the counterexamples expectation in students' responses. Firstly, the parameters of binomial distribution of the correct/incorrect responses are estimated using maximum likelihood estimation. Then, the obtained parameters are used for calculating optimal estimations of probabilities...
Time-of-arrival (TOA) estimator design for impulse radio ultra-wideband (IR-UWB) ranging demands high sampling rate high resolution ADC, which is difficult to implement. Some tradeoffs can be made such as limiting amplitude resolution. In this paper, we propose a two-step threshold selection TOA estimator using a two-bit ADC. The quantization threshold of ADC is set as the coarse threshold to distinguish...
Vehicular Ad hoc Network (VANET), as a subclass of mobile Ad hoc Networks (MANETs), is a promising approach for traffic security, mobile internet and V2V communication. While the packet loss estimation of VANET impacts routing protocol and transmission control algorithm, it turns out to be an important issue. In this paper, we propose an estimation algorithm for packet loss on VANET, RPLE (Real time...
Suppose we have samples of a subset of a collection of random variables. No additional information is provided about the number of latent variables, nor of the relationship between the latent and observed variables. Is it possible to discover the number of hidden components, and to learn a statistical model over the entire collection of variables? We address this question in the setting in which the...
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