This letter features the derivation of a new recursive maximum-likelihood (RML) algorithm. A simplified version of this algorithm is the same as the RML algorithm proposed in [1]. The relative performance of these algorithms is studied with the help of an example in spectral estimation.

The purpose of this letter is to discuss the application of a modified gradient filtering technique proposed by Friedlander [1] to the modified recursive least mean square (RLMS) algorithm of Hsia [2].

The purpose of this paper is to investigate the performance of a typical Doppler processor when the received clutter data is correlated. As the classical theories of statistical inference do not provide a tractable procedure for consideration of correlated non-gaussian random variables, it is necessary to resort to Monte Carlo simulation. A technique based on the theory of Best Linear Prediction followed by an appropriate nonlinear transformation enables consideration of correlated clutter with any arbitrary distribution. It is observed that the processor discussed in the paper exhibits distribution free characteristics in the case of correlated clutter.

A closed form expression is derived for the pull-in range of second-order phase-locked loops (PLL's) with sinusoidal phase detectors. Pull-in range, normalized with respect to gainG, is expressed as a function of the damping factor\zetaand normalized natural frequency β of the linearized loop model. Results are presented for various values of β and\zetaand compared with earlier results.