Frequency estimation (also called post-stratification) is an equating method employed under the common-item nonequivalent groups design. A modified frequency estimation method is proposed here, based on altering one of the traditional assumptions in frequency estimation in order to correct for equating bias. A simulation study was carried out to compare equating errors for the modified frequenc...

In this paper, we consider the problem of frequency estimation of superimposed exponential signals in the presence of multiplicative and additive noise. We propose a subspace method based iterative procedure for estimation of signal frequency parameters. The proposed method is based principal eigenvalue vectors of a special constructed data matrix and the weighted least squares (WLS) techniques...

This paper presents a integer frequency offset (IFO) estimation scheme for the 3GPP long term evolution (LTE) downlink system. Firstly, the conventional joint detection method for IFO and sector cell index (CID) information is introduced. Secondly, an IFO estimation without explicit sector CID information is proposed, which can operate jointly with the proposed IFO estimation and reduce the tim...

This study proposes an effective noise estimation method for robust speech recognition in time-varying noise conditions. The proposed noise estimation scheme employs the Variation Model Composition (VMC) method, where multiple noise models are generated by selectively applying perturbation factors to the mean parameters of a basis noise model. The noise estimate is obtained by using the posteri...

—Orthogonal Frequency Division Multiplexing (OFDM) has been a popular scheme for digital communication systems, which is widely used in digital television and audio broadcasting, wireless networks, powerline networks, and the Fourth Generation (4G) mobile communications. In OFDM scheme, channel estimation is a necessary technique for improving the system’s performance. Linear Least Square (LLS...

background: volume estimation of brain is important for many neurological applications. it is necessary in measuring brain growth and changes in brain in normal/abnormal patients. thus, accurate brain volume measurement is very important. magnetic resonance imaging (mri) is the method of choice for volume quantification due to excellent levels of image resolution and between-tissue contrast. st...

Motion estimation plays a key role in many video applications, such as frame-rate video conversion, video retrieval, video surveillance, and video compression. The key issue in these applications is to define appropriate representations that can efficiently support motion estimation with the required accuracy. In this paper, a low-complexity object motion estimation technique is proposed that i...

new blind estimation of MIMO channels using HGA was proposed for the frequency selective channel. By exploiting the output statistics, an objective function that coming from blind estimation of MIMO channels based on the subspace could be obtained. Then the fitness function based on the objective function is proposed for optimization by a hybrid genetic algorithm (HGA). We have proved this meth...

The aim of this study is to improve the accuracy of flicker parameters estimation in old film sequences in which moving objects are present. Conventional methods tend to fail in flicker parameters estimation due to the effects of moving objects. Our proposed method firstly utilizes an adaptive Gaussian mixture model (GMM)-based method to detect the moving objects in the film sequences, and comb...

the goal of multi-frame super resolution (sr) is to fuse multiple low resolution (lr) images to produce one high resolution (hr) image. the major challenge of classic sr approaches is accurate motion estimation between the frames. to handle this challenge, fuzzy motion estimation method has been proposed that replaces value of each pixel using the weighted averaging all its neighboring pixels i...