One of the major problems in quantum physics has been to generalize classical root-mean-square error measurements obtain an measure satisfying both soundness (to vanish for any accurate measurements) and completeness only measurements). A noise-operator based commonly used this purpose, but it turned out incomplete. Recently, Ozawa proposed a new definition be sound complete. Here, we present n...

Constrained adaptive filtering algorithms inculding constrained least mean square (CLMS), constrained affine projection (CAP) and constrained recursive least squares (CRLS) have been extensively studied in many applications. Most existing constrained adaptive filtering algorithms are developed under mean square error (MSE) criterion, which is an ideal optimality criterion under Gaussian noises....

The ratio-type estimators have been introduced for estimating the mean and total population, but in recent years based on the ratio methods several estimators for population variance have been proposed. In this paper two families of estimators have been suggested and their approximation mean square error (MSE) have been developed. In addition, the efficiency of these variance estimators are com...

Quality of Service (QoS) is the important criteria in the video processing in H.264/AVC Bit-streams. In this paper, the encryption based bit streams transmitted to improve the security of the bit streams. So the proposed system mainly considered reduction of the de-blocking filter effect in the Mean Square Estimation (MSE). The Correlation Motion (CM) based MSE estimation method derives elabora...

Proportionate type adaptive filtering (PtAF) algorithms have been successfully applied for sparse system identification. The major drawback of the traditional PtAF based on the mean square error (MSE) criterion is poor robustness in the presence of abrupt changes because the MSE is valid and rational under Gaussian assumption. However, this assumption is not satisfied in most real-world applica...

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...

Under the assumption that the transmitter FIR multipleinput multiple-output (MIMO) filter is given and FIR left invertible, conditions are derived for when the minimum minimum mean square error (MSE) FIR MIMO filter system does possess the perfect reconstruction (PR) or zero forcing (ZF) property. In most cases, examples using common models for both source coding and communication systems show ...

The Bayesian Ziv–Zakai bound on the mean square error (MSE) in estimating a uniformly distributed continuous random variable is extended for arbitrarily distributed continuous random vectors and for distortion functions other than MSE. The extended bound is evaluated for some representative problems in time-delay and bearing estimation. The resulting bounds have simple closed-form expressions, ...

In modern communication technologies, the demand of image data compression increasing rapidly. This paper presents different methods for image compression like DCT, Walsh, Hadamard and Walsh Hadamard. Main objective of this paper is to achieve the higher compression ratio and lower the Mean square error. Different test images over different orthogonal transform are used to achieve the performan...