A system model for DS-CDMA (Direct Sequence Code Division Multiple Access) is described in its basic form and performance measure based on Mean Square Error (MSE) and Symbol Error Rate (SER) under Additive White Gaussian Noise is performed. For measuring the performance of DS-CDMA receivers, the channel estimate plays for a crucial role and hence the channel estimation for DS-CDMA is considered...

| A lower bound on the mean square error (MSE) of image reconstruction in emission tomography is obtained and used in the evaluation of diierent image approximations. One component of the lower bound on the MSE is the Cram er-Rao (CR) bound on the error variance. The CR bound for diierent image approximations is derived by knowing how the CR bound is modiied when one is interested in some funct...

In this paper, we present performance of pilot based channel estimation techniques such as Least Squares (LS) and Linear Minimum Mean Square Error (LMMSE) for different interpolation methods and modulation schemes. The performance is evaluated using the mean squared error (MSE) as the performance metric of interest for downlink LTE system. Simulation results show that for low SNR environment, a...

In this brief, we develop an least mean square (LMS) algorithm that converge in a statistical sense to the global minimum of the mean square error (MSE) objective function. This is accomplished by estimating the gradient as a smoothed version of the MSE. The smoothed MSE objective begins as a convex functional in the mean. The amount of dispersion or smoothing is reduced, such that over time it...

In this paper, we introduce the diagonal of the modified Riesz distribution defined in 2 , IR  r r . We propose the estimators of different parameters of this new distribution by two method, firstly by the moment method and secondly by the maximum likelihood method. The performance of the both estimators are studied by calculating the Mean Square Error (MSE). KeywordsDiagonal of the modified R...

Wiener filter is widely used for image denoising and restoration. It is alternatively known as the minimum mean square error filter or the least square error filter, since the objective function used in Wiener filter is an age-old benchmark called the Mean Square Error (MSE). Wiener filter tries to approximate the degraded image so that its objective function is optimized. Although MSE is consi...

Component extraction is a technique for extracting the latent components that underlie the observation of a set of variables. In the paper both classical Principal component analysis (PCA) and autoassociative principal component neural network (PCNN) methods with minimum mean square error (MSE) criterion are compared with the corresponding extended component extraction methods with Minimum erro...

This paper mathematically proposes channel estimation algorithms for Cognitive Radio (CR) in terms of Mean Square Error (MSE) and analysis of its Bit Error Rate (BER) performance. As cognitive radio associates itself with the family of opportunistic communication for using frequency spectrum efficiently, issues such as spectrum sensing and channel estimation gain attention. When the main issue ...

This paper points out that the predictability analysis of conventional time series may in general be invalid for long-range dependent LRD series since the conventional mean-square error MSE may generally not exist for predicting LRD series. To make the MSE of LRD series prediction exist, we introduce a generalized MSE. With that, the proof of the predictability of LRD series is presented in Hil...

Robust diffusion algorithms based on the maximum correntropy criterion(MCC) are developed to address the distributed networks estimation issue in impulsive(long-tailed) noise environments. The cost functions used in distributed network estimation are in general based on the mean square error (MSE) criterion, which is optimal only when the measurement noise is Gaussian. In non-Gaussian situation...