Implementation of adaptive fuzzy neuro generalized learning vector quantization (AFNGLVQ) on field programmable gate array (FPGA) for real world application

Microprocessor is needed to be implemented in micro-scale and smaller device cause of its limitation in its resources. One of the microprocessor function is to process a classification and detection method with its inputs. This research is proposed microprocessor design of one of classification algorithm, AFNGLVQ, on FPGA. Compared to its alternative algorithm that has been also implemented in FPGA, FNGLVQ, AFNGLQ gives slightly better result that indicate the algorithm has been successfully implemented in FPGA. The comparison with AFNGLVQ´s higher level language implementation also shows that the FPGA design is worth enough to be implemented in micro-scale devices.