This paper introduces a new computational algorithm for the partial correlation coecients of a linear system given the covariance of its output when excited by a white input noise. Although derived from Levinson's well-known procedure, the proposed algorithm does not make use of the usual parameters in the linear prediction recursion. It may be implemented using xed point arithmetics. Application to speech waves is emphasized. 1

A number of papers have been dealing with the problem of estimating the differential delay of an unknown signal impinging on two sensors. The present contribution deals with the presence of more than one source, which is a case that has never been dealt with before. The solution resorts to slices of high-order spectra, and the full spectral band of the signals is utilized in order to recover the delays. It can be viewed as an improvement to the classical procedure consisting of searching the autocorrelation for local maxima, which does not work when delays are smaller than the source correlation length.

SUMMARYThe transmission-line matrix (TLM) method enables simulation of interior electromagnetic field propagation problems. With the use of absorbent walls, we can simulate exterior problems such as the radiaition of a microstrip antenna. The input impedance is deduced from the standing wave observed in the feedline. The radiation pattern is determined from the field over a plane located in the immediate vicinity of the antenna, using the theory of radiating apertures. However, the CPU time and memory space involved are excessive.Since the radiating structure has several resonant frequencies, it is convenient to apply classical digital signal processing techniques such as finite impulse response filtering associated with a linear prediction method. The present paper focuses on a Prony-Pisarenko method to improve on the TLM method in terms of both computation time and precision of the frequency-domain analysis of the results. In this case, overall CPU time is reduced by a factor of 2 to 3. The paper discusses the results obtained for radiation patterns. This represents a new field of application for the TLM method whose drawbacks are reduced by using appropriate signal processing methods.