Results 11 to 20 of about 248,461 (262)

New robust iterative minimum mean squared error-based interference alignment algorithm

The Journal of Engineering, 2014
Interference alignment (IA) is a promising technique for multiple input multiple output interference channels based systems, achieving the theoretical bound on degrees of freedom.
Sara Teodoro, Adão Silva, Rui Dinis, Daniel Castanheira, Atílio Gameiro   +4 more
doaj   +1 more source

Mid-Term Residential Load Forecasting Based on Neighborhood Component Analysis Feature Selection [PDF]

هوش محاسباتی در مهندسی برق, 2022
Residential load forecasting plays an important role in management and planning in modern smart grids. In planning to keep demand and supply balanced, accurate residential load forecasting is needed.
Iman Bahadornejad, Majid Moazzami, Ghazanfar Shahgholian, Bahador Fani, Mahnaz Hashemi   +4 more
doaj   +1 more source

The Bayesian ABEL Bound on the Mean Square Error [PDF]

2006 IEEE International Conference on Acoustics Speed and Signal Processing Proceedings, 2006
This paper deals with lower bound on the Mean Square Error (MSE). In the Bayesian framework, we present a new bound which is derived from a constrained optimization problem. This bound is found to be tighter than the Bayesian Bhattacharyya bound, the Reuven-Messer bound, the Bobrovsky-Zakai bound, and the Bayesian Cramer-Rao bound.
Renaux, A., Forster, Philippe, Larzabal, Pascal, Richmond, C.   +3 more
openaire   +3 more sources

Defense of the Least Squares Solution to Peelle’s Pertinent Puzzle

Algorithms, 2011
Generalized least squares (GLS) for model parameter estimation has a long and successful history dating to its development by Gauss in 1795. Alternatives can outperform GLS in some settings, and alternatives to GLS are sometimes sought when GLS exhibits ...
Nicolas Hengartner, Toshihiko Kawano, Patrick Talou, Feng Pan, Tom Burr   +4 more
doaj   +1 more source

Load Forecasting Techniques for Power System: Research Challenges and Survey

IEEE Access, 2022
The main and pivot part of electric companies is the load forecasting. Decision-makers and think tank of power sectors should forecast the future need of electricity with large accuracy and small error to give uninterrupted and free of load shedding ...
Naqash Ahmad, Yazeed Ghadi, Muhammad Adnan, Mansoor Ali   +3 more
doaj   +1 more source

Evaluating Gaussian processes for matched-field processing localization using minimum mean squared error criterion [PDF]

JASA Express Letters
Gaussian processes (GPs) can densify and denoise sparsely sampled signals and have been applied in matched-field processing (MFP) localization to improve localization accuracy and robustness.
Shanru Lin, Haiqiang Niu, Peter Gerstoft, Zhenglin Li, Yonggang Guo   +4 more
doaj   +1 more source

An Alternative Ratio-cum-Product Estimator of Population Mean Using a Coefficient of Kurtosis for Two Auxiliary Variates

Data Science Journal, 2010
An alternative ratio-cum-product estimator of population mean using the coefficient of kurtosis for two auxiliary variates has been proposed. The proposed estimator has been compared with a simple mean estimator, the usual ratio estimator, a product ...
Rajesh Tailor, Med Ram Verma, Balkishan Sharma   +2 more
doaj   +1 more source

A Prediction Model of Power Consumption in Smart City Using Hybrid Deep Learning Algorithm

JOIV: International Journal on Informatics Visualization, 2023
A smart city utilizes vast data collected through electronic methods, such as sensors and cameras, to improve daily life by managing resources and providing services. Moving towards a smart grid is a step in realizing this concept.
Salam Abdulkhaleq Noaman, Ali Mohammed Saleh Ahmed, Aseel Dawod Salman   +2 more
doaj   +1 more source

A weighted error-minimizer parameter estimation technique for one-inflated positive Poisson distribution

Results in Control and Optimization
An error-minimizing estimator is always preferred in model fittings. However, each error-minimizing estimator minimizes error differently. This paper combines four error-minimizing estimators, which are root mean-squared error, mean absolute error, root ...
Razik Ridzuan Mohd Tajuddin
doaj   +1 more source

Estimating a Bounded Normal Mean Relative to Squared Error Loss Function [PDF]

Journal of Sciences, Islamic Republic of Iran, 2011
Let be a random sample from a normal distribution with unknown mean and known variance The usual estimator of the mean, i.e., sample mean is the maximum likelihood estimator which under squared error loss function is minimax and admissible ...
A. Karimnezhad
doaj