The complex cepstrum of bicepstrum for system reconstruction with application to sEMG signal

Surface electromyography (sEMG) provides information about the performance of muscles and nerves. An sEMG signal can be modelled as a sum of filtered random impulse processes. The Bispectrum suppresses Gaussian noise and provides the system information only, however, a bispectrum based system reconstruction requires considerable computation. In this paper, we present a new approach to filter response reconstruction from the cepstrum of bispectrum which is computationally simple and performs better than other established methods.