• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.1
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• pp.97-101
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• 2013

There is a growing need for optical communication systems that convert large volumes of data to optical signals and that accommodate and transmit the signals across long distances. Digital optical communication consists of a master unit (MU) and a slave unit (SU). The MU transmits data to SU using digital optical signals. However, digital optical units that are commercially available or are under development transmit data using two's complement representation. At low input levels, a large number of SSOs (simultaneous switching outputs) are required because of the high rate of bit switching in two's complement, which thereby increases the power noise. This problem reduces the overall system capability because a DSP (digital signal processor) chip (FPGA, CPLD, etc.) cannot be used efficiently and power noise increases. This paper proposes a change from two's complement to a more efficient method that produces less SSO noise and can be applied to existing digital optical units.

• 한국데이터정보과학회:학술대회논문집
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• 2005.10a
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• pp.161-169
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• 2005

In this paper we propose a fuzzy c-regression model based on weighted least squares support vector machine(LS-SVM), which can be used to detect outliers in the switching regression model while preserving simultaneous yielding the estimates of outputs together with a fuzzy c-partitions of data. It can be applied to the nonlinear regression which does not have an explicit form of the regression function. We illustrate the new algorithm with examples which indicate how it can be used to detect outliers and fit the mixed data to the nonlinear regression models.