A Complex Lyapunov Theory-based Adaptive Algorithm
نویسنده
چکیده
This paper presents a complex-valued version of the Lyapunov theory-based adaptive filtering algorithm [1]. The resulting algorithm simultaneously updates the real and imaginary parts of the complex coefficients so that the complex error can converge to zero asymptotically. The proposed scheme can be applied to random and deterministic processes because only the desired signal and input signal are required. The design is independent of the stochastic properties of signals and the stability is guaranteed by the Lyapunov Stability Theory. Simulation example is included to demonstrate the performance of the new complex adaptive algorithm.
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