Exponential smoothing technique is one of the most important quantitative techniques in forecasting. The accuracy of forecasting of this technique depends on exponential smoothing constant. Choosing an appropriate value of exponential smoothing constant is very crucial to minimize the error in forecasting. This paper addresses the selection of optimal value of exponential smoothing constant to ...

The purpose of this paper is to present a numerical approach based on the artificial neural networks (ANNs) for solving novel fractional chaotic financial model that represents effect memory and chaos in presented system. method constructed with combination ANNs along Levenberg-Marquardt backpropagation (LMB), named ANNs-LMB. This technique tested problem three cases fractional-order values obt...

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 ...

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...

A technique for designing frames to use with vector selection algorithms, for example Matching Pursuits (MP), is presented. The design algorithm is iterative and requires a training set of signal vectors. An MP algorithm chooses frame vectors to approximate each training vector. Each vector in the frame is then adjusted by using the residuals for the training vectors which used that particular ...

Accurate load prediction is an effective way to reduce power system operation costs. Traditionally, the Mean Square Error (MSE) a common-used loss function guide training of accurate forecasting model. However, MSE unable precisely reflect real costs associated with errors because cost caused by in probably neither symmetric nor quadratic. To tackle this issue, paper proposes generalized cost-o...

The main contributions of this paper can be summarized as follows. First, we compare the Partial Least Squares (PLS) and the Principal Component Analysis (PCA), under fairly general conditions. (In particular, the existence of a true linear regression is not assumed.) We prove that PLS and PCA are equivalent, to within a rst-order approximation, hence providing a theoretical explanation for emp...

The basic goal of region of interest (ROI) based compression for medical image is to enhance the compression efficiency for transmission and storage.Main goal of Region of interest(ROI) compression is to compressROI with supreme quality as compared to other region called Background. For an example, while compressing medical image the diagnostically important region should be compressed with bet...

The present paper is an extension of the work published in Kumar and Vishwakarma (Proceedings theNational Academy Sciences, India, Section A: Physical 90(5): 933-939, 2020). In this paper,various sample allocation schemes are utilized to derive mathematical expressions for mean square errors(MSEs) several well-known estimators population stratified random sampling. Moreover, theeffects various ...

Mainly, the adaptive filters are implemented in time domain which works efficiently in most of the applications. But in many applications the impulse response becomes too large, which increases the complexity of the adaptive filter beyond a level where it can no longer be implemented efficiently in time domain. An example of where this can happen would be acoustic echo cancellation (AEC) applic...