The graphical representation method, Robust CoPlot, is a robust variant of the classical CoPlot method. CoPlot is an adaptation of multidimensional scaling (MDS), and is a practical tool for visual inspection and rich interpretation of multivariate data. CoPlot enables presentation of a multidimensional dataset in a two dimensions, in a manner that relations between both variables and observations to be analyzed together. It has also been used as a supplemental tool to cluster analysis, data envelopment analysis (DEA) and outlier detection methods in the literature. However, this method is very sensitive to outliers. When a multidimensional dataset contains outliers, this can lead to undesirable consequences such as the inaccurate representation of the variables. The motivation is to produce Robust CoPlot that is not unduly affected by outliers. In this study, we have presented a new MATLAB package RobCoP for generating robust graphical representation of a multidimensional dataset. This study serves a useful purpose for researchers studying the implementation of Robust CoPlot method by providing a description of the software package RobCoP; it also offers some limited information on the Robust CoPlot analysis itself. The package presented here has enough flexibility to allow a user to select an MDS type and vector correlation method to produce either classical or Robust CoPlot results.
In time division multiple access (TDMA) communication systems, correctly estimating the synchronization parameters is very important for reliable data transfer. The algorithms used for frequency/phase and symbol timing estimates are generally accepted as knowing the start of signal (SoS) parameter. Therefore, within these parameters, the SoS parameter is of particularly great importance. In this study, a reduced version of the SoS estimation algorithm introduced by Hosseini and Perrins is presented to estimate SoS for Gaussian Minimum Shift Keying (GMSK) modulated signals in burst format over additive white Gaussian noise (AWGN) channels. The reduced algorithm can be implemented on FPGA by using half the number of complex multipliers that would be required by the double correlation method and is robust to carrier frequency/phase errors. Simulations performed under 0.1 normalized frequency offset conditions show that the proposed algorithm has a probability of false lock which is less than 2 7 10 − × , even at 0 dB SNR level.
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