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Embedded DSP applications demand more dynamic range and higher precision to prevent overflow and improve the quality respectively. The most straightforward way to satisfy both is to use the floating-point arithmetic, where the data samples are represented in the exponent and the mantissa parts and the data are normalized for every operation. Designers prefer fixed-point arithmetic with much simpler hardware, but they need to frequently and explicitly scale down the intermediate results to prevent overflow. In this paper, we propose an alternative-static floating-point unit where the operands are represented in the normalized fractional numbers, similar to the mantissa part in the floating-point units. We use static techniques instead to normalize the intermediate values with implicit exponent tracking in our software tool. The simulation result shows that the proposed approach improves both the rounding error and the execution cycles of the fixed-point units with similar hardware complexity.