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The empirical mode decomposition (EMD) is a relatively new method to decompose multicomponent signals that requires no a priori knowledge about the components. In this study, a modified algorithm using raised cosine interpolation is proposed which the authors refer to as raised cosine empirical mode decomposition. The decomposition quality of this proposed technique is controllable via an adjustable...
A signal overlay technique employing the empirical mode decomposition procedure is presented here. A weak narrowband signal is added to the primary signal that shares the same frequency band. Careful signal design reduces interference caused to primary users while ensuring successful recovery of the added signal. At the receiver a stationary filtering approach is ineffective in separating the signals...
A covert communication technique based on the principle of signal overlay is presented here. This technique in its basic form involves a covert transmitter transmitting a message signal that is weak, in relation to, and shares the same frequency band as an existing cover signal. The fact that the two signals overlap in time as well as frequency renders ordinary signal detection techniques ineffective...
A raised cosine filter based interpolation for the empirical mode decomposition (EMD) technique is presented in this paper as an alternative to the cubic spline interpolation used in the original implementation. By adjusting a parameter in the proposed technique one can control the quality of decomposition of the algorithm. This results in superior performance compared to the original approach which...
Empirical mode decomposition (EMD) is a time-frequency analysis technique that has gained popularity in recent times due to its adaptivity and applicability to non-stationary signals. Paired with the Hilbert transform it yields a timefrequency spectrum and is called the Hilbert-Huang transform (HHT). The empirical nature of EMD has resulted in a lack of theoretical analysis so far. Issues regarding...
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