The problem of forming images that are optimal with respect to a Mean Square Error (MSE) criterion, based on nite data, is considered. First, it is shown that the MSE criterion is consistent with the general goal of classifying images, in that decreasing the MSE guarantees a decrease in the probability of misclassifying an image. The problem of choosing sampling locations for image formation th...

The objective of this paper is to implement and evaluate the effectiveness of scaling functions and wavelet transformations in the field of image compression and decompression. The performance parameters like Peak Signal to Noise Ratio (PSNR), Mean Squared Error (MSE), and Compression Ratio(CR),SNR(Signal to Noise Ratio) are calculated based on the Matlab source code. The implemented model prov...

It is known that among all redundancy-free codes (or index assignments), the natural binary code minimizes the mean-squared error (MSE) of the uniform source and uniform quantizer on a binary symmetric channel. We derive a code which maximizes the MSE and demonstrate that the code is linear and its distortion is asymptotically equivalent, as the blocklength grows, to the expected distortion of ...

In this paper, we examine the problem of estimating the sensitive characteristics and behaviors in a multinomial randomized response model using Bayesian approach. We derived a posterior distribution for parameter of interest for multinomial randomized response model. Based on the posterior distribution, we also calculated a credible intervals and mean squared error (MSE). We finally compare th...

In this paper a family of estimators for estimating mean, ratio and product of two means of a finite population has been suggested and studied under the two different situations of random non-response considered by Tracy and Osahan (1994), Singh and Joarder (1998) and Singh, Joarder and Tracy (2000). Asymptotic expressions of biases and mean squared errors of the proposed families have been der...

Vector Quantization is lossy data compression technique and has various applications. Key to Vector Quantization is good codebook. Once the codebook size is fixed then for any codebook generation algorithm the MSE reaches a value beyond which it cannot be reduced unless the codebook size is increased. In this paper we are proposing two-level codebook generation algorithm which reduces mean squa...

We analyze two communication-efficient algorithms for distributed optimization in statistical settings involving large-scale data sets. The first algorithm is a standard averaging method that distributes the N data samples evenly to m machines, performs separate minimization on each subset, and then averages the estimates. We provide a sharp analysis of this average mixture algorithm, showing t...

Alpha-galactosidase production in submerged fermentation by Acinetobacter sp. was optimized using feed forward neural networks and genetic algorithm (FFNN-GA). Six different parameters, pH, temperature, agitation speed, carbon source (raffinose), nitrogen source (tryptone), and K2HPO4, were chosen and used to construct 6-10-1 topology of feed forward neural network to study interactions between...