A Mathematical Theory of Communication
A Mathematical Theory of Communication
Pattern recognition and modern computers
AFIPS '55 (Western) Proceedings of the March 1-3, 1955, western joint computer conference
Empirical explorations of the logic theory machine: a case study in heuristic
IRE-AIEE-ACM '57 (Western) Papers presented at the February 26-28, 1957, western joint computer conference: Techniques for reliability
Use of a computer to design character recognition logic
IRE-AIEE-ACM '59 (Eastern) Papers presented at the December 1-3, 1959, eastern joint IRE-AIEE-ACM computer conference
Pattern recognition and reading by machine
IRE-AIEE-ACM '59 (Eastern) Papers presented at the December 1-3, 1959, eastern joint IRE-AIEE-ACM computer conference
A pattern recognition program that generates, evaluates, and adjusts its own operators
IRE-AIEE-ACM '61 (Western) Papers presented at the May 9-11, 1961, western joint IRE-AIEE-ACM computer conference
Estimation of Mutual Information in Two-Class Pattern Recognition
IEEE Transactions on Computers
Feature Evalution with Measures of Probabilistic Dependence
IEEE Transactions on Computers
Some experiments in spoken word recognition
IBM Journal of Research and Development
On dependence and discrimination in pattern recognition
IEEE Transactions on Computers
| Hi-index | 0.01 |
A computer program has been written to design character recognition logic based on the processing of data samples. This program consists of two subroutines: (1) to search for logic circuits having certain constraints on hardware design, and (2) to evaluate these logics in terms of their discriminating ability over samples of the character set they are expected to recognize. An executive routine is used to apply these subroutines to select a complete logic with a given performance and complexity. This logic consists of 39 to 96 AND gates connected to a shift register and a table look-up or resistance network comparison system. The methods were applied to the design of recognitionl ogics for the 52 upper and lower case characters of IBM Electric Modern Pica type font and lower case Cyrillic characters scanned from Russian text. In both cases when the logics were tested on data different from that used to design the logics, the substitution rate was about one error per thousand. A single logic was designed to read two different Cyrillic fonts. For this design, an error rate of one error per hundred characters was observed. Several experiments are reported ona number of logics designed for typewritten data, and single- and two-font Cyrillic data. The performances of different recognitionsy stems are compared as a function of the complexity of the recognition logics.