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Inspired by recent work in compressive sensing, we propose a framework for the detection of stochastic signals from optimized projections. In order to generate a good projection matrix, we use dimensionality reduction techniques based on the maximization of the mutual information between the projected signals and their corresponding class labels. In addition, classification techniques based on support...
In this paper we considered the problem of performance improvement of known-host-state (quantization-based) watermarking methods undergo additive white Gaussian noise (AWGN) and uniform noise attacks. We question the optimality of uniform high rate quantizer based design of dither modulation and distortion compensate dither modulation methods from their robustness to these attacks point of view in...
In this paper, we address the analysis of the Costa setup under channel uncertainty. Since the Costa setup was entirely considered under the Gaussian assumptions about host and channel statistics, we assume that the channel is an additive white Gaussian noise (AWGN) with unknown variance defined on some interval. First, we solve the problem of average achievable rate optimization assuming that the...
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