1991 nonlinear system analysis and identification from random data technometrics vol 33 no 4 pp 482 483. Describes procedures to identify and analyze the properties of many types of nonlinear systems from random data measured at the input and output points of physical systems improvements are offered in applying older techniques and problems that traditionally have been difficult to analyze are solved by new simpler procedures formulas are stated for optimum nonlinear system identification in . Nonlinear system analysis and identification from random data julius s bendat 1990 new york john wiley xxi 267 pp gbp4995 isbn 0 471 60623 5. Nonlinear system analysis and identification from random data nonlinear system identification wikipedia system identification is a method of identifying or measuring the mathematical model of a system from measurements of the system inputs and outputs the applications of system identification include any system where the inputs and outputs can be measured. We have presented previously a model free characterization of these effects using generic techniques from nonlinear system identification namely a volterra series formulation at the same time buxton et al 1998 described a plausible and compelling dynamical model of hemodynamic signal transduction in fmri