Effective Partitioning of Input Domains for ALM Algorithm

This paper presents a new and simple algorithm for partitioning the input domain for implementation of Active Learning Method (ALM) algorithm. ALM is a pattern-basedalgorithm for soft computing which uses the Ink Drop Spread (IDS) algorithm as its main engine for feature extraction. In thispaper a simple algorithm is introduced with a few computation cost. In order to evaluate the performance of the proposed algorithm, it is applied to two applications, system modeling andpattern recognition. Simulation results show the effectiveness of our algorithm in specifying the appropriate points for dividing the inputs domains

کلیدواژه ها:

Active learning method (ALM) ، fuzzy inference algorithm ، ink drop spread (IDS) ، memristor-crossbar