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This study focuses on a granular representation of signals. The development process dwells upon the use of the principle of justifiable granularity encountered in Granular Computing and the least square error method. This process consists of two phases where the construction of granular representatives of a family of signals (temporal data) is realized by invoking the design at the local and global...
Vector quantization (VQ) is a fundamental and omnipresent mechanism of data compression with various conceptual underpinnings and diversified algorithmic realizations. The objective of this study is to investigate the concept of VQ in the setting of fuzzy sets by forming a coherent algorithmic framework referred to as a fuzzy VQ (FVQ). Given the nature of the framework of VQ in which fuzzy sets are...
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