Non-linear machines as pseudo random pattern generators for digital testing
Date
2003
Authors
Zhong, Jing
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Abstract
Linear machines such as the Linear Feedback Shift Registers (LFSRs) and Linear Hybrid Cellular Automata (LHCA) are often used as Pseudo Random Pattern Generators (PRPGs) in testing of digital circuits. In this thesis, a slightly non-linear machine, the Geffe generator, and its application as a PRPG in testing is investigated. In the research, the randomness properties and the transition properties of the Geffe generator are studied. Theoretical analysis and results of the transition test show that the Geffe generator has a much larger transition capability than the LFSR or LHCA. Fault simulation is also conducted using both the linear and the non-linear machines. Improvements in fault coverage for most ISCAS '89 benchmark circuits show that the non-linear machine, the Geffe generator, exhibits much better performance over the linear machines (the LFSR and LHCA) when it is used as the PRPG to detect stuck-at faults in sequential circuits.
Linear machines such as the Linear Feedback Shift Registers (LFSRs) and Linear Hybrid Cellular Automata (LHCA) are often used as Pseudo Random Pattern Generators (PRPGs) in testing of digital circuits. In this thesis, a slightly non-linear machine, the Geffe generator, and its application as a PRPG in testing is investigated. In the research, the randomness properties and the transition properties of the Geffe generator are studied. Theoretical analysis and results of the transition test show that the Geffe generator has a much larger transition capability than the LFSR or LHCA. Fault simulation is also conducted using both the linear and the non-linear machines. Improvements in fault coverage for most ISCAS '89 benchmark circuits show that the non-linear machine, the Geffe generator, exhibits much better performance over the linear machines (the LFSR and LHCA) when it is used as the PRPG to detect stuck-at faults in sequential circuits.
Linear machines such as the Linear Feedback Shift Registers (LFSRs) and Linear Hybrid Cellular Automata (LHCA) are often used as Pseudo Random Pattern Generators (PRPGs) in testing of digital circuits. In this thesis, a slightly non-linear machine, the Geffe generator, and its application as a PRPG in testing is investigated. In the research, the randomness properties and the transition properties of the Geffe generator are studied. Theoretical analysis and results of the transition test show that the Geffe generator has a much larger transition capability than the LFSR or LHCA. Fault simulation is also conducted using both the linear and the non-linear machines. Improvements in fault coverage for most ISCAS '89 benchmark circuits show that the non-linear machine, the Geffe generator, exhibits much better performance over the linear machines (the LFSR and LHCA) when it is used as the PRPG to detect stuck-at faults in sequential circuits.