Kenneth W. Bauer

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This research demonstrates the adverse implications of using non-robust statistical methods for detecting anomalies in hyperspectral image data, and proposes the use of multivariate outlier detection methods as an alternative detection strategy. Existing outlier detection methods are adapted for use in a hyperspectral image context, and their performance is(More)
In this paper, we present an integrated approach to feature and architecture selection for single hidden layer-feedforward neural networks trained via backpropagation. In our approach, we adopt a statistical model building perspective in which we analyze neural networks within a nonlinear regression framework. The algorithm presented in this paper employs a(More)
This paper describes a new procedure for using control variates in multiresponse simulation when the covariance matrix of the controls is known. Assuming that the responses and the controls are jointly normal, we develop a new unbiased control-variates point estimator for the mean simulation response. We also compute the covariance matrix of this point(More)
The increasing use of steganography requires digital forensic examiners to consider the extraction of hidden information from digital images encountered during investigations. The first step in extraction is to identify the embedding method. Several steganalysis systems have been developed for this purpose, but each system only identifies a subset of the(More)
The proliferation of low-cost IEEE 802.15.4 ZigBee wireless devices in critical infrastructure applications presents security challenges. Network security commonly relies on bit-level credentials that are easily replicated and exploited by hackers. Unauthorized access can be mitigated by physical layer (PHY) security measures that exploit device-dependent(More)