Accession Number : ADA289956

Title :   Probabilistic Modeling and Statistical Inference for Random Fields and Space-Time Processes.

Descriptive Note : Final rept.

Corporate Author : MASSACHUSETTS INST OF TECH CAMBRIDGE LAB FOR INFORMATION AND DECISION SYSTEMS

PDF Url : ADA289956

Report Date : 15 JAN 1995

Pagination or Media Count : 14

Abstract : In this report we summarize the research effort, funded under ONR Grant N00014-91-J-1004, on probabilistic modeling and statistical inference for random fields and space-time processes. The research we have pursued in this project consists of the investigation of a set of interrelated topics involving the development of new mathematical methods for the challenging problems of random field analysis and inference and the application of these methods to problems of practical significance. In particular, the problems of interest in this work were motivated by and directly address issues that are central both to the challenging large-scale data assimilation and estimation problems arising in physical oceanography and to a number of other remote sensing and imaging problems of direct interest to the Navy. (AN)

Descriptors :   *MATHEMATICAL MODELS, *IMAGE PROCESSING, *STATISTICAL INFERENCE, *OCEANOGRAPHIC DATA, ALGORITHMS, DATA PROCESSING, OCEAN CURRENTS, OCEAN SURFACE, PROBABILITY, RESOLUTION, RADAR IMAGES, PATTERN RECOGNITION, COMPUTER VISION, DATA COMPRESSION, COVARIANCE, INVERSE SCATTERING, STATISTICAL PROCESSES, MARKOV PROCESSES, IMAGE RESTORATION.

Subject Categories : Statistics and Probability
      Cybernetics
      Physical and Dynamic Oceanography

Distribution Statement : APPROVED FOR PUBLIC RELEASE