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“…The two thresholds are toggled in a dynamic manner to maximize Pd and minimize Pja such that; when the PU is predicted to be present the smaller threshold is used and vice versa. The two dynamic thresholds are evaluated based upon the noise uncertainty factor which can be estimated using the noise variance history and the noise variances are estimated as [8]. We prove the effectiveness of our proposed algorithm over the conventional energy detector theoretically and through computer simulations.…”

confidence: 88%

“…The two thresholds are toggled in a dynamic manner to maximize Pd and minimize Pja such that; when the PU is predicted to be present the smaller threshold is used and vice versa. The two dynamic thresholds are evaluated based upon the noise uncertainty factor which can be estimated using the noise variance history and the noise variances are estimated as [8]. We prove the effectiveness of our proposed algorithm over the conventional energy detector theoretically and through computer simulations.…”

confidence: 88%

“…Medyan filtresi iki boyutlu bir matris içerisindeki bütün değerleri komşu değerlerle karşılaştırarak tarar ve aritmetik sıraya göre ortanca değeri, taranan değerin yeni değeri olarak atar [26].…”

“…Median filtering is particularly useful in suppressing impulsive noise because it removes effectively the noise amplitude outliers [23,24]. Recently, the combination of finite differences and median filtering has been proposed for estimating the image noise in computer vision algorithms [25] where the signal structures of the underlying image need to be removed. The algorithm DIsCOVER proposed in this work is based on the method considered in Pei et al [25].…”

confidence: 99%

“…Recently, the combination of finite differences and median filtering has been proposed for estimating the image noise in computer vision algorithms [25] where the signal structures of the underlying image need to be removed. The algorithm DIsCOVER proposed in this work is based on the method considered in Pei et al [25]. For DIsCOVER, a set of finite difference operators (FDOs) are used for suppressing the underlying primary signal structures, leaving a set of noise-only series of points where the MLE of the variance can be obtained.…”

confidence: 99%