Variable Length Vector Pattern Recognition.
Abstract
Variable length vector pattern recognition deals with the problem of recognizing words of various symbol lengths (characters, phonemes, etc.) embedded in unsegmented strings of words (sentences, messages, etc.). A mathematical model is developed to describe the generation of such messages, assuming that successive words are chosen independently. A loss function is defined which leads to the development of an iterative decision procedure for minimizing the risk. The computational complexity of this procedure is proportional to message length, whereas the message length would appear exponentially in the expression for computational complexity if the iterative procedure did not exist. Alternative generation models and alternative loss functions can be employed in the development of similar iterative procedures. The optimum iterative procedure was programmed. An illustrative experiment was conducted using the program to compare performance of the procedure with and without segmentation information. (Author)
Document Details
- Document Type
- Technical Report
- Publication Date
- Feb 01, 1971
- Accession Number
- AD0722063
Entities
People
- B. Chandrasekaran
- Kenneth G. Salter
- Thomas J. Harley Jr.