In this work, we address off-line signature verification as a writer-independent system. We propose a set of morphological features, extracted from off-line signature images. To examine the effectiveness of the features, a publicly available signature database, namely CEDAR signature database is used. A pair of signatures is fed to the system to give an inference for their (dis)similarity. To get a compact set of features, a multilayer perceptron based feature analysis technique is utilized. A 10-fold cross-validation framework based on support vector machine is used for verification. Receiver operator curve (ROC) analysis gives an equal error rate (EER) of 11.59%, which is comparable to the state-of-the-arts reported on this database.
The next generation wireless communication system, 5G, or New Radio (NR) will provide access to information and sharing of data anywhere, anytime by various users and applications with diverse multi-dimensional requirements. Physical Uplink Control Channel (PUCCH), which is mainly utilized to convey Uplink Control Information (UCI), is a fundamental building component to enable NR system. Compared to Long Term Evolution (LTE), more flexible PUCCH structure is specified in NR, aiming to support diverse applications and use cases. This paper describes the design principles of various NR PUCCH formats and the underlying physical structures. Further, extensive simulation results are presented to explain the considerations behind the NR PUCCH design.
Abstract. The notion of the proposed methodology is to optimize multidimensional nonlinear problem of conflicting nature that exists among imperceptibility and robustness in image watermarking. The methodology exploits the potentiality of Multi-Objective Genetic Algorithm (MOGA) in searching multiple non-dominated solutions lying on the Pareto front. The characteristics curve of the image are then analyzed and the most appropriate solution is selected using a merit function defined over evaluation measures. The efficacy of the suggested method is demonstrated by reporting the resultant watermarked images and restored watermarks extracted from their mean and median filtered versions.
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