• ETRI Journal
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• v.18 no.3
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• pp.147-160
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• 1996

We investigate noise-induced phase transitions in globally coupled active rotators with multiplicative and additive noises. In the system there are four phases, stationary one-cluster, stationary two-cluster, moving one-cluster, and moving two-cluster phases. It is shown that multiplicative noise induces a bifurcation from one-cluster phase to two-cluster phase. Pinning force also induces a bifurcation from moving phase to stationary phase suppressing the multiplicative noise effect. Additive noise reduces both effects of multiplicative noise and pinning force urging the system to the stationary one-cluster phase. The frustrated effects of pinning force and additive and multiplicative noises lead to a reentrant transition at intermediate additive noise intensity. Nature of the transition is also discussed.

• 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.

• Journal of the Korean Institute of Telematics and Electronics
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• v.25 no.9
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• pp.1019-1026
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• 1988

A parametric detection scheme for determenistic signals is obtained in a generalized observation model which contains non-additive noise. The model employed in this paper includes several special cases such as those describing purely-additive noise, multiplicative noise, and signal dependent noise and allows the consideration of deterministic and random signals. Locally optimum detectors for known deterministic signals in the model are derived and analyzed for performance. It is shown that the locally optimum detectors are interesting generalizations of those for the purely-additive noise model. Performance of the locally optimum detectors designed for the generalized observation model is compared to that of other common detectors.

• 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.

• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.574-576
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• 2004

Since variance of noise is important parameter for a noise filter to reduce noise in image and the performance of noise filter is dependent on estimated variance. In this paper, we apply additive noise variance estimation method to estimate variance of speckle noise of synthetic aperture radar (SAR) imagery. Generally, speckle noise is in multiplicative model, logarithmic transformation is then used to transform multiplicative model into additive model. Here, speckle noise is generally modeled as Gamma distribution function with different looks. The additive noise variance estimation is processed in log domain. The synthesis image and real image of SAR are implemented to test and confirm results and show that more accurate estimation can be achieved.

• 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.

• ETRI Journal
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• v.20 no.2
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• pp.214-230
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• 1998

We investigate noise-induced transitions in active rotator model with a fluctuating threshold in the presence of an additive noise. The fluctuation of the threshold depends on the additive noise in a nonlinear fashion. In the white-noise limit of the fluctuation, the Fokker-Planck equation of the system reduces to that of the system with correlated linear fluctuation implying that the nonlinearity may be transformed into the correlation of linear noises. We also investigate the system with a nonlinear colored noise which depends on the additive noise as its square. The system shows a single peak, two peaks, and three peaks in its steady state probability distribution according to the noise intensities and the correlation time whose change leads to peak-creating, peak-splitting, and peak-merging transitions.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.13 no.4
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• pp.332-339
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• 1988

Using a generalized observation model, in which one can express the effects of non-additive noise such as signal-dependent noise and multiplicative noise in addition to purely-additive noise, the problem of weak random-signal detection is investigated. It is shown that the test statistics of locally optimum detectors for detection of weak random signals in signal-dependent noise model are interesting extensions of those in purely-additive noise model. This result is a complement to the result for weak random-signal detction in multiplicative noise model.

• Korean Journal of Mathematics
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• v.24 no.3
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• pp.447-467
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• 2016

We prove the existence of random attractors for the continuous random dynamical systems generated by stochastic damped plate equations with linear memory and additive white noise when the nonlinearity has a critically growing exponent.

• Proceedings of the IEEK Conference
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• 2000.09a
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• pp.679-682
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• 2000

In this paper, a MMSE filter in homomorphic wavelet transform domain is proposed for restoring an ultrasonic images corrupted by speckle noise. In order to remove effectively the speckle noise which is a kind of multiplicative noise, speckle noise is transformed into a form of additive noise and then the additive noise is denoised through the MMSE filter in homomorphic wavelet transform domain. The proposed method shows much higher quality in terms of ISNR and subject quality.