The integrity and security of fingerprint images can be achieved by using watermarking techniques. We introduce Maximum-Likelihood (ML) watermark detection method to detect an invisible watermark within discrete wavelet transform (DWT) coefficients of fingerprint images. Such an optimum technique, which is based on Bayes’ decision theory and the Neyman-Pearson criterion, requires parameters of ...

A very popular form of hypothesis test is the likelihood ratio test, which is a generalization of the optimal test for simple null and alternative hypotheses that was developed by Neyman and Pearson (We skipped Neyman-Pearson lemma because we are short of time). The likelihood ratio test is based on the likelihood function fn(X−1, · · · , Xn|θ), and the intuition that the likelihood function te...

A new processor for detecting a radar target in correlated, non-Gaussian noise is obtained. When this processor and a matched filter are excited with this noise, performance is improved over that of the matched filter alone. The processor is obtained by developing an approximate, bivariate, probability density for the noise and constructing a Neyman-Pearson test and then using an approximation ...

A physical optics formalism is used to establish a first-principles analysis for discriminating specular returns from diffuse returns in a 1-D synthetic aperture radar. The optimum Neyman-Pearson detection processor is shown to substantially outperform the conventional, full-resolution SAR imager for extended specular targets embedded in diffuse clutter plus receiver noise. Significant performa...

In practical signal detection scenarios, parameters of a random process are often uncertain. In this paper, we model such uncertainties as fuzzy parameters of a stationary random process. A fuzzy Neyman-Pearson hypothesis test concept which accepts any number of fuzzy parameters is presented. A suitable decision rule is developed by applying theory for ordering fuzzy numbers, and stated in term...

The theory of distributed detection is receiving a lot of attention. A common assumption used in previous studies is the conditional independence of the observations. In this paper, the optimization of local decision rules for distributed detection networks with correlated observations is considered. We focus on presenting the detection theory for parallel distributed detection networks with fi...

Distributed spectrum sensing (DSS) is of great importance in Cognitive Radio, especially under fading or shadowing effects. In order to evaluate the performance of a distributed system, it is commonly compared with the centralized system as an upper performance bound. Now the question is whether or not one can obtain a distributed strategy serving as an upper bound to benchmark any distributed ...

Most of the debates around statistical testing suffer from a failure to identify clearly the features specific to the theories invented by Fisher and by Neyman and Pearson. These features are outlined. The hybrids of Fisher’s and Neyman–Pearson’s theory are briefly addressed. The lack of random sampling and its consequences for statistical inference are also highlighted, leading to the recommen...