• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.4C
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• pp.374-378
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• 2003

The asymptotic performance of the two-sample locally optimum rank detector for random signals buried in signal-dependent noise and additive noise is consigered in this paper. It is shown that the locally optimum rank detector, a nonparametric detector, has reasonable asymptotic performance for a class of correlated random signals, compared with the locally optimum detector. It is noteworthy that the the two-sample locally optimum rank detector perform almost the same with the one-sample locally optimum rank detector.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.4C
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• pp.379-383
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• 2003

A simpler nonparametric detector test statistic based on reference observation in addition to the rank statistics of regular observations is suggested in this letter. Using reference observations instead of sign statistics helps us a simpler detector structure especially for random signals buried in multiplicative noise.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.23 no.4
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• pp.796-804
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• 1998

Multiplicative noise is known to be useful in modeling multipath propagation, which is crucial in mobile communication systems analysis. In this paper, nonparametric detection of weak random signals in multiplicative noise is considered. The locally optimum detector based on signs and ranks of observations isderived for good weak-signal detection performance under any noise probability density function. the detector has similarities to the locally optimum detector for random signals in multiplicative noise. It is shown that the nonparametric detector asymptotically hs almost the same performance as the locally optimum detector.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.16 no.4
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• pp.319-325
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• 1991

A nonparametric detection scheme which uses rank statistics for detection of known signals is considered in a special case of a generalized observation model. Specifically locally optimum rank detectors for detection of known deterministic singals in a singnal-dependent noise model are derived, and compared to those derived for the purely-additive noise model. Examples of the score functions are given, which constitutes the test statistics of the locally optimum rank detectors.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.6C
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• pp.541-550
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• 2005

In this paper, we address the derivation of joint distributions and correlation coefficients for four pairs of statistics used commonly in a number of signal detection schemes. The upper and lower bounds of the correlation coefficients are obtained, and interesting relationships between the correlation coefficients are derived. Explicit values of the correlation coefficients are given in the form of tables and figures for easy reference. The results in this paper should be useful in comparing various detection statistics.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.7C
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• pp.633-641
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• 2005

In this paper, we address the derivation of joint distributions and correlation coefficients for three pairs of statistics used commonly in a number of signal detection schemes. The upper and lower bounds of the correlation coefficients for the three pairs are obtained, and interesting relationships between the correlation coefficients are derived. Explicit values of the correlation coefficients evaluated for some meaningful distributions are given in the form of tables and figures for easy reference. The results in this paper should be useful in comparing various detection statistics.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.23 no.6
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• pp.1454-1460
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• 1998

In this ppaer, we propose a new detector based on the median-shift sign, and then investigate its asymptotic and finite sample-size performance. We call it the median-shift sign (MSS) detector, which is an extension of the classical sign detector. First, we consider the asymptotic opti$$\mu$ median shift values and their characteristics. Next, we consider the asymptotic relative efficiency of the MSS detectors. we then consider the problem of detecting known signals in noise of known probability density function, and the problem of detecting known signals when only partial information is available on the noise.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.37 no.1
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• pp.76-82
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• 2000

In this paper, we consider nonparametric signal detection problems under the presence of additive noise exhibiting weak dependence We derive the test statistics of the locally optimum rank detectors under a weakly dependent noise model for known and random signal cases The performance characteristic of the locally optimum rank detectors are analyzed in terms of asymptotic relative efficiency.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.22 no.7
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• pp.1543-1549
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• 1997

In this paper, rank-based nonparmetric detection of composite signals in additive noise is considered. Based on signs and ranks of observations, the locally optimum detector is deived for weak-signal detection under any specified noise probability density funhction. This detector has similarities to the locally optimum detector for comjposite signals in additive noise. The asymptotic performance of this nonparametric detector is shown to be as good as that of the locally optimum detector.