Fixed-point computing with variable fraction length for motion profile generation
2016
This paper proposes a new fixed-point computing method for motion profile generation. When parameters have wide ranges, floating-point computing usually is used for accurate computation; however, this method increases execution time. In the proposed method, by considering input data, optimum fraction lengths are determined for different parameters. In this way, the fixed-point computing offers an accurate computation in a minimum execution time. Experimental results show the performance of the proposed method.
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