Conditionally Linear and Non-Gaussian Processes
A new theory and corresponding methodology is evolving for certain classes of nonlinear non-Gaussian signal processing. This research considers particular statistical model structures such as conditionally linear or bilinear. Some non-Gaussian distributions, which arise in underwater acoustical signal processing, are included, as are others. The results are based on rigorous developments related to, but not limited to, bilinear and conditionally Gaussian processes. Parameter or state estimation (e.g., acoustic source location) are studied as well as preliminary results in information transmission and coding.
Unable to display preview. Download preview PDF.
- 3.T.U. Halawani, R.R. Mohler and W.J. Kolodziej, “A Two-Step Bilinear Filtering Approximation,” IEEE Trans. Acous., Sp. & Sig. Proc., Vol. ASSP-32, pp. 244–352, 1984.Google Scholar
- 4.R.R. Mohler, W.J. Kolodziej, H.D. Brunk and R.S. Engelbrecht, “On Nonlinear Filtering and Tracking,” in Signal Processing in the Ocean Environment, ( E.J. Wegman, Ed.), Marcel-Dekker, New York, 1984.Google Scholar
- 5.W.J. Kolodziej and R.R. Mohler, “Analysis of a New Nonlinear Filter and Tracking Methodology,” IEEE Trans. Infor. Theory, Vol. IT-29, 1984, to appear.Google Scholar
- 9.W.J. Kolodziej and R.R. Mohler, “State Estimation and Control of Conditionally Linear Systems,” to appear, SIAM J. Control & Optimization, Vol. 25, 1985.Google Scholar