We consider estimation of a set of tent-map chaotic sequences. These sequences are obtained by iterating a one dimensional chaotic function in the (-1,1) domain. We demonstrate how to construct a set of n sequences, in which information in the form of n arbitrary samples in the (-1,1) domain is embedded. Additionally the signs of all sequences jointly form a valid digital codeword. Each sequence in the set consists of m elements, hence the set of sequences is equivalent to a rate \lm analog error correcting-code. We present performance in terms of coding gain when maximum likelihood (ML) and minimum-mean-square-error (MMSE) estimation approaches are employed.

This contribution focuses on error-correcting codes for analog signals. Generally, error-correcting codes exhibit a threshold effect, which degrades performance at the low SNR range. We propose two error correction alternatives based on chaotic dynamical systems, which improve threshold performance relative to previously proposed methods. The first one, which is based on principles of diversity, exhibits a very simple decoder. The second alternative, which is based on a low-density parity-check code, attains a significantly lower threshold. Theoretical analysis and simulations are provided.

This paper focuses on error-correcting codes for analog signals. Generally, error-correcting codes exhibit a threshold effect, which degrades performance at the low signal-to-noise ratio (SNR) range. We propose two error-correction alternatives based on chaotic dynamical systems, which improve threshold performance relative to previously proposed methods. The first one, which is based on principles of diversity, exhibits a very simple decoder. The second alternative, which is based on a low-density parity-check (LDPC) code, attains a significantly lower threshold. Theoretical analysis and simulations are provided.