The robustness of a subspace generalized likelihood ratio test (GLRT) detector to signal mismatch is addressed for data conforming to the generalized multivariate analysis of variance model. This model assumes a deterministic signal of known form in the presence of unknown, colored, Gaussian noise. The subspace GLRT compresses data into a lower-dimensional subspace prior to detection. It is sho...

A performance analysis of likelihood ratio test (LRT)-based and generalized likelihood ratio test (GLRT)based array receivers for the detection of a known real-valued signal corrupted by a potentially noncircular interference is considered in this paper. The distribution of the decision statistics associated with the LRT and GLRT is studied. This allows us to give exact closed-form expressions ...

Detecting a transient signal of unknown arrival time in noise is actually a binary hypothesis test problem, where the null hypothesis (noise only) is a simple one, while the alternative hypothesis is composite. The generalized likelihood ratio test (GLRT) is a common tool to solve such problems. In this paper we show how order statistics (OS) approach can be used to solve the same problem. We s...

Generalized likelihood ratio test (GLRT) for directional residual based fault isolation is studied in this paper. The conditional probability of correct fault isolation is used to measure the performance of the test. The explicit form of this probability is derived with the help of two GLRT invariant properties and the standard fault isolation subspace. The effect of linear transformation is st...

The generalized likelihood ratio test (GLRT), which is commonly used in composite hypothesis testing problems, is investigated. Conditions for asymptotic optimality of the GLRT in the NeymanPearson sense are studied and discussed. First, a general necessary and sufficient condition is established, and then based on this, a sufficient condition, which is easier to verify, is derived. A counterex...

A generalized likelihood-ratio test (GLRT) detector is derived for detecting a spacetime signal in the presence of unknown subspace interference and unknown target doppler. The near optimality and constant false alarm rate (CFAR) property of the GLRT is shown by the relationship to the uniformly most powerful invariant (UMPI) test using a simple approximation. Examples are presented comparing t...

In this paper, we reconsider the problem of detecting a matrix-valued rank-one signal in unknown Gaussian noise, which was previously addressed for case sufficient training data. We relax above assumption to limited re-derive corresponding generalized likelihood ratio test (GLRT) and two-step GLRT (2S–GLRT) based on certain unitary transformation It is shown that re-derived detectors can work w...

Detection of anomalous network traffic is accomplished using a generalized likelihood ratio test (GLRT) applied to traffic arrival times. The network traffic arrival times are modelled using a Markov modulated Poisson process (MMPP). The GLRT is implemented using an estimate of the MMPP parameter obtained from training data that is not anomalous. MMPP parameter estimation is accomplished using ...

Cognitive radio network is one of the prime solutions of band width crises problem. To resolve band width crises firstly we have to sense primary user (PU) licensed signal. To sense PU signal there are various sensing techniques which have been proposed by researchers, but each of them are having some limitations. In this paper we present a two stage detector for spectrum sensing (SS) in cognit...

The majority of fMRI studies obtain functional information using statistical tests based on the magnitude image reconstructions. Recently, a complex correlation (CC) test was proposed based on the complex image data in order to take advantage of phase information in the signal. However, the CC test ignores additional phase information in the baseline component of the data. In this paper, a new ...