The generation of binary and near-binary pseudorandom signals: an overview

Pseudorandom signals have been widely used for system identification. Maximum length binary (MLB) signals are the best known class of pseudorandom signals, because of their ease of generation using feedback shift registers, but it is less well known that there are several other classes of binary and near-binary signals with identical, or nearly identical properties. An overview of these classes of signals is given, and the design of a new MATLAB routine incorporating all these classes of signals is described. The importance of the choice of MLB signal to use in particular applications is illustrated with the identification of a Wiener system having a quadratic nonlinearity and a cubic nonlinearity. Using correlation analysis to estimate the linear system weighting function, errors due to the nonlinearities can be reduced if an appropriate choice is made of feedback connections and of data length used for the estimation.