Based on data provided from various power plants, several statistical signal processing algorithms were developed, that adaptively predict the total heat required to produce a given amount of electricity under certain parametric constraints. The algorithms were programmed in 'C' and displayed highly satisfactory results. Adaptive Signal Processing by Particle Filters and Discounting of Old Measurements. Prof. P.M. Djuric, as the chief investigator, we have developed adaptive estimation methods in a Bayesian methodology using Monte Carlo sampling, in which it is possible to give unequal importance to older measurements. It has been shown that, the results obtained are identical to conventional adaptive methods with forgetting factors for linear models.
Further investigation is in progress.
A Novel Multi-user Detector for CDMA Systems. A new and interesting approach has been applied to develop a multi-user detector, which exhibits significantly better performance than most known detectors. For the cases we have tested, the detector shows excellent near-far resistance and negligible degradation in performance for increasing number of users. Further work is in progress. Submitted to the Transactions in Signal Processing, Jan 2001.