TRAINABLE ADAPTIVE FOCUSED REPLICATOR NETWORK FOR ANALYZING DATA

Electronic data is classified using adaptive focused replicator networks (AFRNs). AFRNs are sets of array elements, each array element being trainable in order to replicate a predetermined sub-group of data. Unknown data is inputted into each and every array element in an AFRN array and then replica...

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Bibliographische Detailangaben
1. Verfasser:	MALYJ, WASYL
Format:	Patent
Sprache:	eng ; fre ; ger
Schlagworte:	CALCULATING COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS COMPUTING COUNTING ELECTRIC COMMUNICATION TECHNIQUE ELECTRICITY HANDLING RECORD CARRIERS IMAGE DATA PROCESSING OR GENERATION, IN GENERAL INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTEDFOR SPECIFIC APPLICATION FIELDS PHYSICS PICTORIAL COMMUNICATION, e.g. TELEVISION PRESENTATION OF DATA RECOGNITION OF DATA RECORD CARRIERS
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Beschreibung
Zusammenfassung:	Electronic data is classified using adaptive focused replicator networks (AFRNs). AFRNs are sets of array elements, each array element being trainable in order to replicate a predetermined sub-group of data. Unknown data is inputted into each and every array element in an AFRN array and then replicated by each element array. A comparison is made for each array element to determine the accuracy of each replication. If only one array element successfully replicates the unknown data, then the unknown data is classified in accordance with the corresponding predetermined sub-group of data.