• The Journal of Korean Institute of Communications and Information Sciences
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• v.16 no.5
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• pp.445-448
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• 1991

The two-sample locally optimum rank detection scheme is obtained which uses rank and sign statistics for detection of random signals in additive noise. It is shown that the detector is similar in structure to the locally optimum detector for random signals and to the one-sample locally optimum rank detector for random signals. It is also shown that the detector is a generalization of the two-sample locally optimum rank detector for known signals. In addition , the problem of two-sample locally optimum rank detection of random signals in multiple input case is considered briefly.

• 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.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.16 no.3
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• pp.219-231
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• 1991

In this paper, various results on Iocally optimum detection of signals are reviewed concisely, which are easlily apphcable to weak signal detection problems. In addition, locally optmum rank detection schemes for weak signals are reviewed, which are nonparametric counterparts of the locally optimum detecturs. Examples of practical applications, problems in implementation dnd performance characteristecs of the locally optimum detectors are also discussed, Finally, a fuzzy extension of the generalized Neyman Pearson lemma is briefly discussd.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.17 no.8
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• pp.789-795
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• 1992

The generalized Neyman-Pearson lemma Is reformulated In the framework of the fuzzy set theory. Based on the result, we define the locally optimum fuzzy test and derive the locally optimum fuzzy test function. As a pratical application of the locally optimum fuzzy test, detection of weak deterministic signals corrupted by purely-adative noise Is considered, which Is an important problem In statistical signal processing. Comparisons between the locally optimum and the locally optimum fuzzy tests are also made.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.15 no.11
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• pp.955-961
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• 1990

Test statistics are obtained for detection of weak signals in signal-dependent noise using rank statistics. A generalized model is used in this paper in order to consider non-additivenoise as well as purely-additive noise. Locally optimum rank detectors for the model are shown to have similarity to locally optimum detectors and to be generalizations of these for the purely-additive noise model. A similar result is obtained for multi-input cases.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.10C
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• pp.973-980
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• 2006

In most of the studies on locally optimum detection assumes independent observations. The use of an independent observation model may cause a considerable performance degradation in detection applications of modern high data rate communication systems exhibiting dependence among interference components. In this paper, we address the detection of weak known signals in multiplicative and first order Markov additive noises. In Part 1, the test statistics of the locally optimum detectors are investigated in detail. In Part 2, the asymptotic and finite sample-size performance of several detectors are obtained and compared, confirming that the dependence among interference components need to be taken into account to maintain performance appropriately.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.16 no.11
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• pp.1117-1124
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• 1991

Locally optimum detectors are useful for detection of signals with small strength, but it is often difficult to implement the exact form of the locally optimum nonlinearity. In this paper, a suboptimum quantizer detection system in which the locally optimum nonlinearity is replaced by a uniform quantizer and a coder is proposed. The proposed system does not require iteration to obtain the quantizer parameters and is easily implementable.

• 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.

• Proceedings of the Korean Institute of Communication Sciences Conference
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• 1991.10a
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• pp.107-110
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• 1991

When the noise has both additive and signal-dependent components, locally optimum detector test statistics are obtained for detection of weak composite signals using the generalized Neyman-Pearson lemma. In order to consider the non-additive noise as well as purely-additive noise, a generalized observation model is used in this paper. The locally optimum detector test statistics are derived for several different cases according to the relative strengths of the known signal component, the random signal component, and the signal-dependent noise component. Schematic diagrams of the locally optimum detector structures are also included.

• 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.