Low-power driven state assignment of finite state machines

2002 ◽  
Author(s):  
Tzong-Dar Her ◽  
Wei Kang Tsai ◽  
F. Kurdahi ◽  
Yulin Chen
Keyword(s):  
Low Power ◽  
Finite State Machines ◽  
State Machines ◽  
State Assignment ◽  
Finite State

scholarly journals Pioneer: A New Tool for Coding of Multi-Level Finite State Machines Based on Evolution Programming

VLSI Design ◽  
1994 ◽  
Vol 2 (2) ◽  
pp. 105-116
Author(s):  
S. Muddappa ◽  
R. Z. Makki ◽  
Z. Michalewicz ◽  
S. Isukapalli
Keyword(s):  
Finite State Machines ◽  
Mutation Rates ◽  
Natural Phenomenon ◽  
State Machines ◽  
State Assignment ◽  
Wide Range ◽  
Finite State ◽  
Multi Level ◽  
Crossover And Mutation ◽  
Evolution Programs

In this paper we present a new tool for the encoding of multi-level finite state machines based on the concept of evolution programming. Evolution programs are stochastic adaptive algorithms, based on the paradigm of genetic algorithms whose search methods model some natural phenomenon: genetic inheritance and Darwinian strife for survival. Crossover and mutation rates were tailored to the state assignment problem experimentally. We present results over a wide range of MCNC benchmarks which demonstrate the effectiveness of the new tool. The results show that evolution programs can be effectively applied to state assignment.

State assignment in finite state machines for minimal switching power consumption

1994 ◽  
Vol 30 (8) ◽  
pp. 627-629 ◽  
Author(s):  
S.K. Hong ◽  
I.C. Park ◽  
C.M. Kyung ◽  
S.H. Hwang
Keyword(s):  
Power Consumption ◽  
Finite State Machines ◽  
State Machines ◽  
State Assignment ◽  
Switching Power ◽  
Finite State
Sign in / Sign up

Export Citation Format

Share Document