DocumentCode :
3479276
Title :
Singular value decomposition FPGA implementation for tactile data processing
Author :
Ibrahim, Ali ; Valle, Maurizio ; Noli, Luca ; Chible, Hussein
Author_Institution :
COSMIC Lab., Univ. of Genova, Genoa, Italy
fYear :
2015
fDate :
7-10 June 2015
Firstpage :
1
Lastpage :
4
Abstract :
Embedded electronic systems for tactile data processing capture the attention of recent researchers because of its importance in many domains. Machine learning based on tensorial kernel approach has proven its effectiveness in processing tactile information. Computing tensorial kernel corresponds to computing the singular value decomposition. This paper presents an FPGA implementation of singular value decomposition for tensorial kernel computation. The design is implemented for an arbitrary m×n matrix with fixed point arithmetic. The results figure out a tradeoff between the accuracy of computation and the input data resolution. The experimental results demonstrate the efficiency of our design by increasing the accuracy of computation and by providing comparable results in terms of time latency.
Keywords :
field programmable gate arrays; fixed point arithmetic; learning (artificial intelligence); matrix algebra; singular value decomposition; FPGA implementation; arbitrary matrix; embedded electronic systems; fixed point arithmetic; machine learning; singular value decomposition; tactile data processing; tensorial kernel computation; Computer architecture; Field programmable gate arrays; Jacobian matrices; Kernel; Matrix decomposition; Singular value decomposition; Symmetric matrices; Embedded electronic systems; One sided Jacobi algorithm; SVD FPGA implementation; Tensorial kernel;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
New Circuits and Systems Conference (NEWCAS), 2015 IEEE 13th International
Conference_Location :
Grenoble
Type :
conf
DOI :
10.1109/NEWCAS.2015.7182094
Filename :
7182094
Link To Document :
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