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Architecture design for a multi-sensor information fusion processor
Sereati C.O.a, Sumari A.D.W.a, Adiono T.a, Ahmad A.S.a
a School of Electrical Engineering and Informatics, Institut Teknologi Bandung, Bandung, Indonesia
[vc_row][vc_column][vc_row_inner][vc_column_inner][vc_separator css=”.vc_custom_1624529070653{padding-top: 30px !important;padding-bottom: 30px !important;}”][/vc_column_inner][/vc_row_inner][vc_row_inner layout=”boxed”][vc_column_inner width=”3/4″ css=”.vc_custom_1624695412187{border-right-width: 1px !important;border-right-color: #dddddd !important;border-right-style: solid !important;border-radius: 1px !important;}”][vc_empty_space][megatron_heading title=”Abstract” size=”size-sm” text_align=”text-left”][vc_column_text]© 2019 Universitas Ahmad Dahlan.This paper discusses the design of the architecture of an information fusion processor. This processor emulates the way of human thinking, namely by drawing conclusions from the obtained collection of information. Architecture design for this processor is based on Knowledge Growing System (KGS) algorithm. KGS is a novelty in Artificial Intelligence field. Compared to other AI methods, KGS focuses on the observation of the process of the knowledge growth within human brain based on information received from the surrounding environment. By using KGS algorithm, this processor works by receiving inputs from a set of sensors and possible hypotheses obtained after the processing of the information. The processor generates a value which is called as Degree of Certainty (DoC), which show the most possible hypothesis among all alternative ones. The Processor Elements which are used to perform KGS algorithm is designed based on systolic array architecture. The design of this processor is realized with VHSIC Hardware Design Language (VHDL) and synthesized by using FPGA Quartus II.13.1. The results show that the data path which has been design is able to perform the mechanism of KGS computation.[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Author keywords” size=”size-sm” text_align=”text-left”][vc_column_text][/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Indexed keywords” size=”size-sm” text_align=”text-left”][vc_column_text]Artificial intelligence,Information fusion,Knowledge growing system,Processor design,VHDL[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Funding details” size=”size-sm” text_align=”text-left”][vc_column_text][/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”DOI” size=”size-sm” text_align=”text-left”][vc_column_text]https://doi.org/10.12928/TELKOMNIKA.v17i1.10180[/vc_column_text][/vc_column_inner][vc_column_inner width=”1/4″][vc_column_text]Widget Plumx[/vc_column_text][/vc_column_inner][/vc_row_inner][/vc_column][/vc_row][vc_row][vc_column][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][/vc_column][/vc_row]