ABSTRACT
Once laser speckle appearance is intrinsically granular, it is possible to suggest a similarity with the basis of the new granular computing (GrC) paradigm. Granular computing term dates from 1970s, when it was proposed by Zadeh in his early works on fuzzy sets. The intrinsic dynamic characteristic of the laser speckle patterns, the processing of time history speckle pattern (THSP) signals with temporal GrC. The granular transformation of THSP is considered a convenient approach to deal with these complex signals. Both classes of sets (level fuzzy sets) could be used in the present application to simplify the computation in specific speckle activity classification. Distinct examples of fuzzy temporal granulation can be found in the literature, applied to find similarity between time series; describe time series, such as ECG signals, and time series analysis. The granular computing is presented as a novel methodology, which converts the THSP signal in a set of information granules.
