Paper Title: PHASE RECOVERY OF A STOCHASTIC POINT PROCESS SYSTEM Technical Area: Spectrum Estimation and Processing

In this work we present two algorithms for the estimation of the phase of a neuroelectric system of point processes using the third-order spectral density function of the output. The neuroelectric system, which is called muscle spindle, plays an important role in the initiation of the movement and the maintenance of the posture. The system can be modelled with the help of a linear stochastic model. The phase of the transfer function is estimated with the help of the third-order spectral density function of the output. The estimate of the third-order spectral density function is obtained by smoothing the third-order modified periodogram statistic. As illustrative examples we examine the behavior of the muscle spindle under two different conditions: (a) when it is affected by a gamma motoneuron and (b) when it is affected by an alpha motoneuron. It is shown that in the first case there is a delay of the output by about 12 ms whereas in the second case the system is delayed for about 37 ms.