Constrained Sequence Generation Using Stochastic Sequential Machines
نویسندگان
چکیده
In power estimation, one is faced with two problems: 1) generating input vector sequences that satisfy a given statistical behavior (in terms of signal probabilities and correlations among bits); 2) making these sequences as short as possible so as to improve the efficiency of power simulators. Stochastic sequential machines (SSMs) can be used to solve both problems. In particular, this paper presents a general procedure for SSM synthesis and describes a new framework for sequence characterization to match designer’s needs for sequence generation or compaction. Experimental results demonstrate that compaction ratios of 1-3 orders of magnitude can be obtained without much loss in accuracy of total power estimates.
منابع مشابه
Stochastic Sequential Machines Synthesis with Application to Constrained Sequence Generation
In power estimation, one is faced with two problems: 1) generating input vector sequences that satisfy a given statistical behavior (in terms of signal probabilities and correlations among bits); 2) making these sequences as short as possible so as to improve the efficiency of power simulators. Stochastic sequential machines (SSMs) can be used to solve both problems. In particular, this paper p...
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تاریخ انتشار 1996