THE OPTIMUM METHOD OF PATTERN RECOGNITION FOR MUTUALLY CORRELATED CHARACTERISTICS (OB OPTIMALNOM METODE OPOZNANIYA OBRAZOV PRI VZAIMNOKORRELIROVANNYKH PRIZNAKAKH),
Abstract
In various papers dealing with the design of recognition machines the undimensional distribution functions are established after sampling, then assuming the characteristics are truly independent, the multidimensional distribution function is found. In this case the machine applies the minimization of error probability. In practice, however, it is in general impossible to establish a sufficiently complete system of uncorrelated characteristics. Consequently, the present author discards the statistical approach. The optimization criterion of the recognition machine is sought in the minimum of the number of standards needed for comparison (i.e., the simplicity of the recognizing device) rather than in the minimum of the error probability. The minimum of the number of standards is found by means of the so-called association function. Each point in the space of the characteristics is described by the totality of standard-associating functions. The standard-associating function of an arbitrary pattern is positive if the point of the space of characteristics under consideration is closer to that standard than an arbitrary realization of another pattern; otherwise, the associating function is equal to zero.
Document Details
- Document Type
- Technical Report
- Publication Date
- Nov 16, 1967
- Accession Number
- AD0674317
Entities
People
- I. T. Turbovich
Organizations
- National Air and Space Intelligence Center