• Journal of Electrical Engineering and Technology
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• v.10 no.3
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• pp.1201-1211
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• 2015

WSN acts as an effective tool for tracking the large scale environments. In such environment, the battery life of the sensor networks is limited due to collection of the data, usage of sensing, computation and communication. To resolve this, a mobile robot is presented to identify the data present in the partitioned sensor networks and passed onto the sink. In novel data collection algorithm, the performance of the data collecting operation is reduced because mobile robot can be used only within the limited range. To enhance the data collection in a changing environment, Non Linear Error Identifier (NLEI) algorithm has been developed and presented in this paper to configure the robot by means of error models which are non-linear. Experimental evaluation has been conducted to estimate the performance of the proposed NLEI and it has been observed that the proposed NLEI algorithm increases the error correction rate upto 42% and efficiency upto 60%.

• Journal of Communications and Networks
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• v.1 no.2
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• pp.118-133
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• 1999

In this paper we compare linear and non-linear inter-ference cancellation for systems employing code division multi-ple access (CDMA) techniques. Specifically, we examine linear and non-linear parallel interference cancellation(also called multi-stage cancellation) in relationship to other multiuser detection al-gorithms. We show the explicit relationship between parallel inter-ference cancellation and the decorrelator (or direct matrix inver-sion). This comparison gives insight into the performance of paral-lel interference cancellation (PIC) and leads to vetter approaches. We also show that non-linear PIC approaches with explicit chan-nel setimation can provide performance improvement over linear PIC, especially when using soft non-linear symbol estimates. The application of interference cancellation to non-linear modulation techniques is also presented along with a discussion on minimum mean-squared error(MMSE) symbol estimation techniques. These are shown to further improve the performance of parallel cancella-tion.

• Journal of the Korean Data and Information Science Society
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• v.15 no.4
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• pp.899-910
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• 2004

In this paper we have proposed a new loss function, namely, non-linear exponential(NLINEX) loss function, which is quite asymmetric in nature. We obtained the Bayes estimator under exponential(LINEX) and squared error(SE) loss functions. Moreover, a numerical comparison among the Bayes estimators of power function distribution under SE, LINEX, and NLINEX loss function have been made.

• Journal of Electrical Engineering and Technology
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• v.4 no.2
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• pp.229-233
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• 2009

This paper proposes a correction method for the error inherently created by time-step approximation in finite element analysis (FEA). For a simple RL and RLC linear circuit, the error in time-step analysis is analytically investigated, and a correction method is proposed for a non-linear system as well as a linear one. Then, for a practical inductor model, linear and non-linear time-step analyses are performed and the calculation results are corrected by the proposed methods. The accuracy of the corrected results is confirmed by comparing the electric input and output powers.

• Journal of Electrical Engineering and Technology
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• v.8 no.3
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• pp.658-665
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• 2013

While the chirp signal is extensively used in radar and sonar systems for target decision in wireless communication systems, it has not been widely used for positioning in indoor environments. Recently, the IEEE 802.15.4a standard has adopted the chirp spread spectrum (CSS) as an underlying technique for low-power and low-complexity precise localization. Chirp signal based ranging solutions have been established and deployed but their ranging performance has not been analyzed in multipath environments. This paper presents a ranging performance analysis of a chirp signal and suggests a method to suppress multipath error by using a type of non-linear chirp signal. Multipath ranging performance is evaluated using a conventional linear chirp signal and the proposed non-linear chirp signal. We verify the feasibility of both methods using two-ray multipath model simulation. Our results demonstrate that the proposed non-linear chirp signal can successfully suppress the multipath error.

• Journal of Advanced Marine Engineering and Technology
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• v.27 no.5
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• pp.641-647
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• 2003

The use of infrared range-finder sensor as the environment recognition system for mobile robot have the advantage of low sensing cost compared with the use of other vision sensor such as laser finder CCD camera. However, it is not easy to find the previous works on the use of infrared range-finder sensor for a mobile robot because of the non-linear characteristic of that. This paper describes the error due to non-linearity of a sensor and the correction of it using neural network. The neural network consists of multi-layer perception and Levenberg-Marquardt algorithm is applied to learning it. The effectiveness of the proposed algorithm is verified from experiment.

• Communications for Statistical Applications and Methods
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• v.2 no.2
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• pp.296-302
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• 1995

When heteroscedasticity occurs in random effects linear model, the error variance may depend on the values of one or more of the explanatory variables or on other relevant quantities such as time or spatial ordering. In this paper we derive a score test as a diagnostic tool for detecting non-constant error variance in random effefts linear model based on the model expansion on error variance. This score test is compared to loglikelihood ratio test.

• Communications for Statistical Applications and Methods
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• v.8 no.2
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• pp.327-336
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• 2001

This work concerns estimating a regression function, which is not linear, using aggregate data. In much of the empirical research, data are aggregated for various reasons before statistical analysis. In a traditional parametric approach, a linear estimation of the non-linear function with aggregate data can result in unstable estimators of the parameters. More serious consequence is the bias in the estimation of the non-linear function. The approach we employ is the kernel regression smoothing. We describe the conditions when the aggregate data can be used to estimate the regression function efficiently. Numerical examples will illustrate our findings.

• Journal of the Korean Society for Precision Engineering
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• v.23 no.12 s.189
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• pp.72-79
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• 2006

Vibration of a non-linear system under random parametric excitations was evaluated by probabilistic methods. The non-linear characteristic terms of a system structure were quasi-linearized and excitation terms were remained as they were An analytical method where the square mean of error was minimized was used An alternative method was an energy method where the damping energy and restoring energy of the linearized system were equalized to those of the original non-linear system. The numerical results were compared with those obtained by Monte Carlo simulation. The comparison showed the results obtained by Monte Carlo simulation located between those by the analytical method and those by the energy method.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2006.05a
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• pp.113-114
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• 2006

Vibration of a non-linear system under random excitations was evaluated by probabilistic methods. The non-linear characteristic terms of a system structure were quasi-linearized and excitation terms were remained as they were. An analytical method where the square mean of error was minimized was used. An alternative method was an energy method where the damping energy and restoring energy of the linearized system were equalized to those of the original non-linear system. The numerical results were compared with those obtained by Monte Carlo simulation. The comparison showed the results obtained by Monte Carlo simulation located between those by the analytical method and those by the energy method.