Normally distributed data arises in various contexts and often one is interested in estimating its variance. The authors limit themselves in this chapter to the class of estimators that are (positive) multiples of sample variances. Two important qualities of estimators are bias and variance, which respectively capture the estimator’s accuracy and precision. Apart from the two classical estimato...

An almost unbiased estimator using known value of some population parameter(s) is proposed. Under simple random sampling without replacement (SRSWOR) scheme the expressions for bias and mean square error (MSE) are derived. Numerical illustrations are given.

Estimation problems with bounded, uniformly distributed noise arise naturally in reconstruction problems from over complete linear expansions with subtractive dithered quantization. We present a simple recursive algorithm for such bounded-noise estimation problems. The mean-square error (MSE) of the algorithm is “almost” (1 ), where is the number of samples. This rate is faster than the (1 ) MS...

— New bounds on the rate distortion function of certain non-Gaussian sources, with a proportional-weighted mean-square error (MSE) distortion measure, are given. The growth, g, of the rate distortion function, as a result of changing from a non-weighted MSE distortion measure to a proportional-weighted distortion criterion is analyzed. It is shown that for a small distortion, d, the growth, g, ...

JPEG is a standard compression algorithm used to reduce memory requirement for the storage of digital images. The JPEG standard allows to specify the desired quality of the encoded image by varying a quality factor (QFactor) between 0 (lowest quality) and 100 (perfect image-no compression). It is of interest to be able to assess the quality of a JPEG image. A common and very effective way for t...

Regression analysis is a statistical technique that most commonly used for forecasting. Data sets are becoming very large due to continuous transactions in today's high-paced world. The data difficult manage and interpret. All the independent variables can’t be considered prediction because it costs high maintenance of set. A novel algorithm has been implemented this paper. Its emphasis on extr...

This paper presents a Comparative Study of NLMS (Normalized Least Mean Square) and ENSS (Error Normalized Step Size) LMS (Least Mean Square) algorithms. For this System Identification (An Adaptive Filter Application) is considered. Three performances Criterion are utilized in this study: Minimum Mean Square error (MSE), Convergence Speed, the Algorithm Execution Time. The Step Size Parameter (μ...

The constant modulus algorithm (CMA) is an e ective technique for blind receiver design in practice. Treating CMA as a linear estimation problem, e ects of noise and channel conditions are investigated. For the class of channels with arbitary nite impulse responses, an analytical description of locations of constant modulus receivers and an upper bound of their mean squared errors (MSE) are der...

The rapid time-variation of a fading multipath environment can impair the performance of multiple-input multiple-output orthogonal frequency division multiplexing (MIMO OFDM). This paper proposes a pilot placement method for MIMO OFDM systems under time-varying channels with the guard band. The time-varying channel is described by complex exponential basis expansion model (BEM). We discuss the ...

In this paper, we present the steady state analysis of adaptive IIR notch filters based on the least mean -power error criterion. We consider the cases when the sinusoidal signal is contaminated with white Gaussian noise and . We first derive two difference equations for the convergence of the mean and the Mean Square Error (MSE) of the adaptive filter’s notch coefficient, and then give the ste...