least mean square error function
Denoising ECG Signal using Adaptive Filter Al...
... (Least Mean Square), NLMS (Normalized Mean Square), and RLS (Recursive Least ...Normalized mean square error was calculated and our MATLAB simulation results ...
10
A COMPARATIVE ANALYSIS OF MEAN SQUARE ERROR ADAPTIVE FILTER ALGORITHMS FOR GENERATION OF MODIFIED SCALING AND WAVELET FUNCTION
... Where is the step size parameter and controls the convergence characteristics of the LMS algorithm; is the mean square error between the output y(n) and the reference signal. The LMS algorithm is ...
6
Performance Evaluation of MMSE and LS Channel Estimation in OFDM System
... transfer function of these radio channels is unequal in time as well as in frequency domain, due to which a dynamic estimation of these channels should required at the demodulation point of ...aided Least ...
5
ABSTRACT : Adaptive filter algorithm is a widely used method in communication systems, control systems, digital
... objective function, the error signal is ...objective function will help the adaptive-filter output signal to match with the desired ...the error signal is formed and optimized to find the ...
7
SECRET DATA HIDING BY OPTIMIZING GENERAL SMOOTHNESS DIFFERENCE EXPANSION BASED METHOD
... (TRAINLM) function and INITNW and TRAINS functions are used for adaptation of ...like mean square error, mean absolute error, sum square error and root mean ...
9
Mean square error optimal weighting for multitaper cepstrum estimation
... Cepstrum-based methods are important in many applica- tions, especially speech analysis [1], and also in other areas such as, e.g., seismic deconvolution [2], vibratory diagno- sis using mechanical signals [3], and ...
11
Study of cost functions in three term backpropagation for classification problems
... study Mean Square Error, Bernoulli Cost Function of Chow et ...Cost Function of Shamsuddin et al. (2001) and Improved Cost Function of Zhang et ...cost function were ...
23
Adaptive linear filtering design with minimum symbol error probability criterion
... minimum mean square error (MMSE) criterion and has found ever-increasing applications in ...symbol error rate (MSER) criterion for communication ...symbol error over the MMSE ...density ...
13
Least Mean Square (LMS) for Smart Antenna
... the error signal between filter output and desired signal d(n) at time n, and u(n) is the transmitted ...update function for the LMS algorithm, where µ is the rate of adaptation, controlled by the ...
6
Spectral Estimation And Supervised Classification Technique For Real Time Electromyography Pattern Recognition
... of mean square error for 21 mother wavelets function 75 ...wavelets function 77 4.3 Mean square error performance of Daubechies6 for 13 ...
24
IJCSMC, Vol. 6, Issue. 1, January 2017, pg.23 – 29 An Efficient Hybrid Approach for Secure Speech Cryptography
... of mean square error and peak signal to noise ratio parameters in case of RSA, DES and Hybridization algorithms concludes that The mean square error is less in case of Hybrid ...
7
Performance Analysis of LMS and Normalized LMS Adaptive Filter Algorithms
... plot mean of LMS filter is moving to the left (negative mean) and Mean moves to the right (Positive Mean) in Normalized ...the mean value of the ...the mean value and less ...the ...
7
Pilot Placement for Time Varying MIMO OFDM Channels with Virtual Subcarriers
... the least square (LS) channel estimation to obtain the minimum mean square error (MSE) and derive the pilot allocation that can satisfy the minimum MSE with regard to guard band in ...
8
Evaluation of growth stage specific crop coefficients of maize using weighing lysimeter
... The NSE and RSR values also indicated that the dual crop coefficient (DCC) performed ‘Very Good’ in estimating the seasonal evapotranspiration of maize (Table 2). However, with respect to different growth stages, ...
6
Implementation of Inventory Management System in a Furniture Company: A Real Case study
... use mean absolute percentage error (MAPE) in the measurement of forecast accuracy because it was considered asymmetric in that ‘equal errors above the actual value result in a greater APE than those below ...
18
Statistical Study of Least Mean Square and Normalised Least Mean Square Algorithms
... ABSTRACT: This paper studies the stochastic behavior of the LMS and NLMS algorithms for a system identification framework when the input signal is a cyclostationary white Gaussian process. The input cyclostationary ...
8
Post-processing through linear regression
... The classical linear regression approach of ensemble re- gression is based on ordinary least-square (OLS) fitting. This approach has some weaknesses which can be detrimental in the context of ensemble ...
14
Development of a Computer Aided System for Swine Flu Prediction using Computional Intelligence
... This section covers the cross authentication between existing and proposed techniques. Some familiar algorithms parameters have been chosen to show that the performance of the proposed algorithm is superior to the ...
7
Estimation under a Finite Mixture of Exponentiated Exponential Components Model and Balanced Square Error Loss
... on square error loss function and objective prior, are used to obtain estimators based on balanced square error loss function for the parameters, survival and hazard rate ...
11
Improved least mean square algorithm with application to adaptive sparse channel estimation
... its mean square error (MSE) lower bound has a direct relationship with finite impulse response (FIR) channel ...using least-absolute shrink- age and selection operator ...
18