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The estimation approach discussed in this paper is based on a signal-theoretic and statistical analysis of the notion of orientation. In contrast to other approaches, it does not require the computation of gray value gradients, or the power spectrum of the given signal patch, or quadrature filter outputs, but directly estimates a small central part of the autocovariance function (acf) of the signal...
This paper concerns the application of modern computational control tools in a special class of power electronic circuits, namely switch-mode dc-dc converters. Specifically, we aim at developing a disturbance estimation scheme that can be used in addition to recently developed explicit MPC control schemes in order to achieve offset-free output voltage reference tracking in the presence of unknown...
The bootstrap technique is a well-known method to generate multiple versions of predictors with the same structure. In this paper two different nonlinear structures are considered: neural networks and regression trees. They are both applied on real data related to the problem of predicting state bond price on the basis of the value of the previous auction and some financial indicators. Bootstrap is...
While practically applying polynomial methods for design of sampled-data systems attention must paid to the structure of the transfer matrices. The paper considers the specialities of the factorization procedure of rational transfer matrices in connection with the solution of H2 — and associated H∞ — optimization problems for sampled-data systems on the basis of the Wiener-Hopf method.
Due to the improvements in computational speed and the development of effective solvers for nonlinear optimization problems, optimization-based state estimation has become an interesting alternative to common approaches such as the Extended Kalman Filter. Nevertheless the computational effort to solve the optimization problem may cause problems in the online application to chemical processes, especially...
Recursive sparse parameter estimates obtained using the author's recent maximum a posteriori (MAP) approach, where the sparse parameter estimates are determined as the a posteriori mode of a Gaussian sum filter, are compared with a new maximum probability (MP) methodology, where the sparse parameter estimates are determined as the component of a Gaussian sum filter with the highest a posteriori weighting...
In this paper, we propose a novel method to estimate the direction of arrival (DOA) of the harmonic acoustic signals received by a uniform linear sensor array. The wideband Direction of Arrival (DOA) estimation problem is formulated under Bayesian framework. The received signals are firstly divided into narrow sub-bands, and the sparsity in the angular domain in each sub-band is exploited to give...
A new method for blind separation of multiple communication signals received by a single sensor is presented in this paper. Based on the different rates and waveforms of communication signals, we employ oversampling and singular value decomposition (SVD) to turn a single demixing problem into the estimation problem of waveform and symbol that can be solved by conventional independent component analysis...
A novel sparse representation-based method for two-dimensional (2-D) direction-of-arrival (DOA) estimation with L-shaped array is proposed. In our method, the 2-D DOA estimation is cast as a reconstituted problem of sparse matrix. The model for sparse-matrix reconstitution is first presented based on the cross-correlation matrix. Then an extended orthogonal matching pursuit (EOMP) algorithm is put...
This work investigates the problem of estimating the K frequency components of a mixture of complex sinusoids. Component frequencies of practical signals are not assumed to lie on a specified grid, but any values in the normalized frequency domain (0, 1). To estimate the off-grid frequencies, we apply the first Taylor expansion to approximate the true unknown dictionary and establish a more accurate...
A new algorithm using modified propagator for two-dimensional (2D) central DOA estimation of coherently distributed (CD) noncircular (NC) sources impinging on the L-shaped array structured by two uniform linear arrays (ULAs) is proposed. Without the computationally intensive and time-consuming estimation of sample covariance matrix and eigendecomposition process, the proposed algorithm estimates the...
Problem of pilot contamination and blind spatial filtering for massive MIMO is considered in this paper. Blind spatial filtering method based on MUSIC angle of arrival (AoA) estimation is proposed as a possible solution for this problem. And error distribution is examined with respect of channel angular spread. Spatial properties of the telecommunication channels such as angular spread affect the...
In this article, a novel low-complexity block-processing sparse system estimation method, based on least squares (LS), ℓ1-norm minimization and support shrinkage, is proposed. The proposed method can be seen as a counterpart for the Least Absolute Shrinkage and Selection Operator (LASSO), in the sense that the proposed method aims to find the vector that minimizes its ℓ1-norm subject to a maximum...
One of the key challenges to enable high data rates in the downlink of LTE-Advanced (LTE-A) is the precoding and receiver design. In this work, we focus primarily on the UE and the base station (BS) processing, particularly on estimating and using the interference resulting from strong neighboring stations. In this paper, we propose a novel receiver design that performs well in the presence of interference...
Recently, various techniques using cyclic redundancy check (CRC) codes for error correction have been proposed. In previous techniques, a small number of unreliable bits in a packet were toggled in order to change negative acknowledgement (NAK) into acknowledgement (ACK). The difficulty of using these techniques is that the worst case complexity is still high because the number of possible error patterns...
Smart eyeglasses or head-mounted displays (HMDs) have been gaining traction as next-generation mainstream wearable devices. However, previous HMD systems [1] have had limited application, primarily due to their lacking a smart user interface (Ul) and user experience (UX). Since HMD systems have a small compact wearable platform, their Ul requires new modalities, rather than a computer mouse or a 2D...
Having not the apriority knowledge about the DSSS signal in the non-cooperation condition, we proposed a Non-Supervised neural network algorithm to detect and identify the PN sequence. A cognitive learning algorithms for estimation the direct sequence spread spectrum (DSSS) signal pseudo-noise (PN) sequence is presented. The non-supervised learning algorithm is proposed according to the Kohonen rule...
The performance of any machine based recognition system heavily depends on the types of features used. More accurate the features extracted are, better is the chance of getting enhance performance in the recognition system. With this aim in mind a feature extraction method is proposed for numerals of Indian languages. It has been observed that structural feature are having an edge over the statistical...
In this paper, a method of estimating true motion vectors to reduce image quality deterioration such as block artifact is proposed. Three consecutive original input images are used to calculate the motion vectors. Among consecutive input images, the first and third frames are used to conduct interpolation and the block unit PSNR of the created interpolated frame and the second frame which is an original...
Smart antenna technology in cellular communication is an auspicious method to enhance the potential of communications networks. One of the problematic issues in smart antenna is the inaccurate detection of the arrival signal with different angles of arrival in multipath Rayleigh fading channel. In this paper, a new smart antenna signal processing method has been proposed for estimating the angle-of-arrival...
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