Optimal Harmonic Filters Design Based Mean Value Estimation of the Source and Load Characteristics

2012 ◽  
Vol 5 (2) ◽  
pp. 155-163 ◽  
Author(s):  
Mohamed T. Elmathana ◽  
Ahmed F. Zobaa ◽  
Yasser Hegazy
Keyword(s):  
Mean Value ◽  
Value Estimation ◽  
Load Characteristics

Mean value—estimation and a few properties

2019 ◽  
pp. 16-21
Author(s):  
Steve Selvin
Keyword(s):  
Mean Value ◽  
Analytic Tool ◽  
Value Estimation ◽  
The Mean

The mean value is perhaps the most fundamental statistic and the chapter describes its properties and features that make it an important and necessary analytic tool.

scholarly journals Design of Chaotic Bifurcation Parameter Modulation Scheme using Mean Value Estimation

2018 ◽  
Vol 1 (1) ◽  
pp. 52-61
Author(s):  
Hikmat Najem Abdullah ◽  
Ibrahim Fahmi Ali
Keyword(s):  
Spread Spectrum ◽  
Chaotic Map ◽  
Mean Value ◽  
Direct Sequence Spread Spectrum ◽  
Modulation Scheme ◽  
Manufacturing Cost ◽  
Bifurcation Parameter ◽  
Parameter Modulation ◽  
Value Estimation ◽  
Chaotic Parameter

In this paper, the bifurcation parameter of the chaotic map is estimated accurately by utilizing the ergodic properties of a chaotic dynamical signal. Binary Phase Shift Keying Ergodic Chaotic Parameter Modulation (BPSK-ECPM) scheme is used to modulate the information signal in the bifurcating parameter of the chaotic map. A mean value estimation technique is used at the receiver to retrieve the original information accurately. This method minimizes the computational complexity of the receiver; thereby, reduces the total manufacturing cost. Simulation results confirm that, in AWGN channel and at bit error rate (BER) of 10-3, BPSK-ECPM achieves gains in Eb/N0 of about 0.7dB and 5dB in comparison with conventional direct sequence spread spectrum with BPSK modulation (DS-SS BPSK) and conventional ergodic chaotic parameter modulation spread spectrum (ECPM-SS) systems respectively. The results also confirm that in Rayleigh fading channel and at BER of 10-3, BPSK-ECPM achieves gains in Eb/N0 of about 6.3dB and 1.6dB in comparison with DS-SS BPSK and ECPM-SS systems respectively, which make BPSK-ECPM an ideal candidate for the intelligent transportation system (ITS).  

A batch means procedure for mean value estimation of processes exhibiting long range dependence

2003 ◽  
Author(s):  
A. Suarez-Gonzalez ◽  
J.C. Lopez-Ardao ◽  
C. Lopez-Garcia ◽  
M. Rodriguez-Perez ◽  
M. Fernandez-Veiga ◽  
...  
Keyword(s):  
Long Range ◽  
Mean Value ◽  
Long Range Dependence ◽  
Batch Means ◽  
Value Estimation

Mean Value Estimation from Digital Computer Simulation

1966 ◽  
Vol 14 (1) ◽  
pp. 25-44 ◽  
Author(s):  
A. V. Gafarian ◽  
C. J. Ancker
Keyword(s):  
Computer Simulation ◽  
Digital Computer ◽  
Mean Value ◽  
Value Estimation

scholarly journals Histogram Publication over Numerical Values under Local Differential Privacy

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Xu Zheng ◽  
Ke Yan ◽  
Jingyuan Duan ◽  
Wenyi Tang ◽  
Ling Tian
Keyword(s):  
Privacy Preservation ◽  
Differential Privacy ◽  
Frequency Estimation ◽  
Mean Value ◽  
Distributed Data ◽  
Distributed Environment ◽  
Real World Data ◽  
Multiple Queries ◽  
Optimal Resource ◽  
Value Estimation

Local differential privacy has been considered the standard measurement for privacy preservation in distributed data collection. Corresponding mechanisms have been designed for multiple types of tasks, like the frequency estimation for categorical values and the mean value estimation for numerical values. However, the histogram publication of numerical values, containing abundant and crucial clues for the whole dataset, has not been thoroughly considered under this measurement. To simply encode data into different intervals upon each query will soon exhaust the bandwidth and the privacy budgets, which is infeasible for real scenarios. Therefore, this paper proposes a highly efficient framework for differentially private histogram publication of numerical values in a distributed environment. The proposed algorithms can efficiently adopt the correlations among multiple queries and achieve an optimal resource consumption. We also conduct extensive experiments on real-world data traces, and the results validate the improvement of proposed algorithms.

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