Use of procedural programming languages for controlling production systems

Author(s):  
T. Ishida ◽  
Y. Sasaki ◽  
Y. Fukuhara
Author(s):  
Sergey Yu. Smogluk ◽  
Eugeniy N. Garin ◽  
Daria S. Romanova

The article presents a programming paradigm that defines a new style of program development called procedural-parametric programming (PPP). The paradigm is based on parametric polymorphism, which allows the procedures to accept and process variant data types without the algorithmic choice of alternatives within these procedures. In procedural programming languages, such types are described by unions (union in C, C++) or variant entries (in Pascal). Algorithmic processing of variants is carried out by means of conditional operators or switches. This approach is a development of procedural programming methods and acts as an alternative to object-oriented programming. The procedural-parametric paradigm of programming is an extension of the procedural approach. It makes possible to increase the capabilities of the latter by supporting data polymorphism. The application of the proposed approach will allow to increase the functional capabilities of the procedures without making any internal algorithmic changes. Procedural-parametric programming can be used both independently and in combination with other programming paradigms


Author(s):  
H. BUNKE ◽  
J. DVORAK

In this paper, we discuss how rule based expert system shells can be used in pattern recognition for the implementation of algorithms which are procedurally oriented in their nature rather than rule based, and have traditionally been implemented in procedural programming languages. Particular examples include finite state automata, context free parsing, string matching, graph matching and discrete relaxation.


Filomat ◽  
2007 ◽  
Vol 21 (1) ◽  
pp. 67-86 ◽  
Author(s):  
Predrag Stanimirovic ◽  
Milan Tasic ◽  
Predrag Krtolica ◽  
Nikolas Karampetakis

We investigate two algorithms for computing the Moore-Penrose and Drazin inverse of a given one-variable polynomial matrix by interpolation. These algorithms differ in the method used for constant matrices inverses computing. The first algorithm uses the Grevile?s method, and the second one uses the Leverrier-Faddeev method and its generalization. These algorithms are especially useful for symbolic computation in procedural programming languages. We compare results by implementing the algorithms in the programming package MATHEMATICA and in the procedural programming languages DELPHI and C++.


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