Reinventing Fpga Optimised Stochastic Computing Convolutional Neural Network Architecture for Highly Efficient Artificial Intelligence Workload

Lee, Yang Yang; Wahab, Mohd Nadhir Ab; Halim, Zaini Abdul

doi:10.2139/ssrn.4385482

Cited by 1 publication

(1 citation statement)

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“…A FPGA is a type of integrated circuit that contains programmable logic gates, memory, and other elements on a chip. FPGAs are used in a wide range of applications, including security [46,47], image processing [48,49], face and object recognition [50][51][52][53][54][55][56][57][58][59][60][61][62][63][64], quantum computing [65][66][67][68][69][70][71][72][73][74][75][76][77], and artificial intelligence [64,[78][79][80][81][82][83][84][85][86]. To demonstrate the performance of the system and filter, we used a Zynq-7000 FPGA [78,79,87].…”

Section: Fpga Implementationmentioning

confidence: 99%

FPGA to study the behavior of a maneuvering UGV using sliding innovation filter

Al-Shabi

Bonny

Gadsden

2023

Signal Processing, Sensor/Information Fusion, and Target Recognition XXXII

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Field programmable gate arrays (FPGAs) are increasingly popular due to their customizability, which enables them to be tailored to specific applications, resulting in minimal resource usage that saves energy and space. In this work, we used an FPGA with a Z-board from Xilinx to simulate the application of the sliding innovation filter (SIF) to a robotic arm. SIF is a predictor-corrector filter used for both linear and nonlinear systems to estimate states and/or parameters. It shares similar principles with sliding mode observer and smooth variable structure filter (SVSF) and uses a correction gain derived to satisfy Lyapunov stability, keeping the estimates near the measurements. We tested SIF on a manipulator with two joints (rotational and prismatic), using FPGA to run the simulation while tracking resource utilization. We compared the results with those of SVSF.

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