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Fast Neural Network Training on FPGA Using Quasi-Newton Optimization Method

Fast Neural Network Training on FPGA Using Quasi-Newton Optimization Method

Price : 14000

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Course Duration
Approx 10

Course Price
₹ 14000

Course Level
Beginner

Course Content

Fast Neural Network Training on FPGA Using Quasi-Newton Optimization Method

Abstract

In this brief, a customized and pipelined hardware implementation of the quasi-Newton (QN) method on field-programmable gate array (FPGA) is proposed for fast artificial neural networks onsite training, targeting at the embedded applications. The architecture is scalable to cope with different neural network sizes while it supports batch-mode training. Experimental results demonstrate the superior performance and power efficiency of the proposed implementation over CPU, graphics processing unit, and FPGA QN implementations.

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