Engineering topics
Publications and source records attributed to Whitsitt, S. J..
Variance relationships among certain count estimators and posterior probability estimators of probability of correct classification are investigated. An estimator using posterior probabilities is presented for use in stratified sampling designs. A test case involving three normal classes is examined.
Methods of efficiently generating and classifying samples with specified multivariate normal distributions were discussed. Conservative confidence tables for sample sizes are given for selective sampling. Simulation results are compared with classified training data. Techniques for comparing error and separability measure for two normal patterns are investigated and used to display the relationship between the error and the Chernoff bound.
Two problem areas are often encountered in the use of multispectral scanner data: (1) large quantities of man and machine time are required to analyze and store the volumes of data gathered and (2) the quality of the data is usually reduced by the introduction of unwanted random noise. This paper will present some effects of data compression and random noise on multispectral data, particularly as they apply to pattern recognition and picture quality.