International Journal of Reconfigurable and Embedded Systems (IJRES)
Vol 13, No 2: July 2024

Implementation of first order statistical processor on FPGA for feature extraction

Hadiyoso, Sugondo (Unknown)
Ramdani, Ahmad Zaky (Unknown)
Irawati, Indrarini Dyah (Unknown)
Wijayanto, Inung (Unknown)



Article Info

Publish Date
01 Jul 2024

Abstract

Statistical calculations on signals commonly used in feature extraction. In software processing, statistical computation is an easy task. However, providing a computer requires high costs for simple statistical processing. Another consideration is the need for implementation with real-time and portable processing. Therefore, an alternative device is needed, one of which is the field programmable gate array (FPGA). FPGA is a logic circuit board that can be reconfigured according to computing needs. FPGA can also be used as a prototyping of electronic chips. However, implementing statistical formulas in FPGA is interesting in developing its architecture. Therefore, this research proposes a logic circuit design that can be used for first-order statistical calculations. Statistical parameters include the mean, variance, standard deviation, skewness, and kurtosis. The validation test was performed on the electrocardiogram (ECG) signal series and compared with manual calculations. Validation shows that the mean and variance has very high accuracy with an average error of less than 0.06%.

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Journal Info

Abbrev

IJRES

Publisher

Subject

Economics, Econometrics & Finance

Description

The centre of gravity of the computer industry is now moving from personal computing into embedded computing with the advent of VLSI system level integration and reconfigurable core in system-on-chip (SoC). Reconfigurable and Embedded systems are increasingly becoming a key technological component ...