Estimation of average switching activity in combinational and sequential circuits
DAC '92 Proceedings of the 29th ACM/IEEE Design Automation Conference
Power estimation methods for sequential logic circuits
IEEE Transactions on Very Large Scale Integration (VLSI) Systems
Trace-driven steady-state probability estimation in FSMs with application to power estimation
Proceedings of the conference on Design, automation and test in Europe
Sequential Circuit Design Using Synthesis and Optimization
ICCD '92 Proceedings of the 1991 IEEE International Conference on Computer Design on VLSI in Computer & Processors
Markovian analysis of large finite state machines
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
A Probabilistic Method for the Computation of Testability of RTL Constructs
Proceedings of the conference on Design, automation and test in Europe - Volume 1
Low power finite state machine synthesis using power-gating
Integration, the VLSI Journal
Sequential algorithm for low-power encoding internal states of finite state machines
Journal of Computer and Systems Sciences International
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In this work we describe an approach that implicitly formulates and solves the Chapman-Kolmogorov equations that describe the state probabilities associated with the stationary behavior of sequential circuits. Unlike previous approaches that assumed uncorrelated input signals, we model the more general case where the sequential circuit is driven by a sequence of inputs described by a discrete time Markov chain. This Markov chain is described implicitly using a formalism that allows for a compact description of chains with an exponentially high number of states. Using this approach, we present an application in power estimation of sequential circuits that takes into account all the temporal and spatial correlations between the primary inputs and the internal signals. We present results showing that, in some cases, it is possible to solve exactly the Chapman-Kolmogorov equations for systems with more than 107 equations.