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This paper applies stochastic theory to the design and implementation of field-oriented control of an induction motor drive using a single field-programmable gate array (FPGA) device and integrated neural network (NN) algorithms. Normally, NNs are characterized as heavily parallel calculation algorithms that employ enormous computational resources and are less useful for economical digital hardware...
The FPGA (field programmable gate arrays) is concurrent, executing all its logic in parallel, therefore is good for neural network applications that are characterized as heavy parallel calculation algorithms. The stochastic arithmetic can simplify the computation elements and is compatible with modern VLSI design. This paper presents an efficiency approach for a single FPGA to implement the field-oriented...
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