A Simple Algorithm for Fitting a Gaussian Function

Guo, Hongwei

doi:10.1002/9781118316948.ch31

Cited by 62 publications

(71 citation statements)

References 3 publications

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“…Gaussian peaks [15] can be matched our results of connectivity better than other mechanisms. We have the equation for a Gaussian model is: SN number (τ): the τth highest connection probability to BS …”

Section: Connectivity Experiments and Approximationsupporting

confidence: 73%

Realistic Analysis of Energy Efficiency in Multihop Wireless Sensor Networks

Jing

Aida

2014

IEICE Trans. Inf. & Syst.

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SUMMARYAs one of the most widely investigated studies in wireless sensor networks (WSNs), multihop networking is increasingly developed and applied for achieving energy efficient communications and enhancing transmission reliability. To accurately and realistically analyze the performance metric (energy efficiency), firstly we provide a measurement of the energy dissipation for each state and establish a practical energy consumption model for a WSN. According to the analytical model of connectivity, Gaussian approximation approaches to experimental connection probability are expressed for optimization problem on energy efficiency. Moreover, for integrating experimental results with theories, we propose the methodology in multihop wireless sensor networks to maximize efficiency by nonlinear programming, considering energy consumptions and the total quantity of sensing data to base station. Furthermore, we present evaluations adapting to various wireless sensor networks quantitatively with respect to energy efficiency and network configuration, in view of connectivity, the length of data, maximum number of hops and total number of nodes. As the consequence, the realistic analysis can be used in practical applications, especially on self-organization sensor networks. The analysis also shows correlations between the efficiency and maximum number of hops, that is the multihop systems with several hops can accommodate enough devices in ordinary applications. In this paper, our contribution distinguished from others is that our model and analysis are extended from experiments. Therefore, the results of analysis and proposal can be conveniently applied to actual networks.

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Section: Connectivity Experiments and Approximationsupporting

confidence: 73%

Realistic Analysis of Energy Efficiency in Multihop Wireless Sensor Networks

Jing

Aida

2014

IEICE Trans. Inf. & Syst.

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show abstract

“…Nevertheless, given that there is more data in the tail of the Gaussian than in the bell, weighting the sample points by its correspondent estimation balance the influence of the entire data set during the minimization of the sum of square errors. This is known as weighted least-square minimization (see [5]). …”

Section: Fitting a Gaussian Functionmentioning

confidence: 99%

Learning the Temperature Dynamics During Thermal Laser Ablation

Fichera

2016

Springer Theses

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“…Because this method uses the logarithm of data, it is clear that error creates if the observed data contains a zero value. To avoid these deficiencies we used Guos model, [4].…”

Section: Caruanas Algorithmmentioning

confidence: 99%

“…In the case that there is an additive random noise η [4], the data, we observe, are not the ideal value f (x) but…”

Section: Guos Alghorithmmentioning

confidence: 99%