Inclusion functions and global optimization 11
Mathematical Programming: Series A and B
Constraint arithmetic on real intervals
Constraint logic programming
Analytical fault modeling and static test generation for analog ICs
ICCAD '94 Proceedings of the 1994 IEEE/ACM international conference on Computer-aided design
Fault-based automatic test generator for linear analog circuits
ICCAD '93 Proceedings of the 1993 IEEE/ACM international conference on Computer-aided design
LIMSoft: Automated Tool for Design and Test Integration of Analog Circuits
Proceedings of the IEEE International Test Conference on Test and Design Validity
Analog Circuit Testing Based on Sensitivity Computation and New Circuit Modeling
Proceedings of the IEEE International Test Conference on Designing, Testing, and Diagnostics - Join Them
An Integrated Approach for Analog Ciruit Testing with a Minmum Number of Detected Parameters
Proceedings of the IEEE International Test Conference on TEST: The Next 25 Years
Test Vector Generation for Linear Analog Devices
Proceedings of the IEEE International Test Conference on Test: Faster, Better, Sooner
Methods and Applications of Interval Analysis (SIAM Studies in Applied and Numerical Mathematics) (Siam Studies in Applied Mathematics, 2.)
ICCAD '97 Proceedings of the 1997 IEEE/ACM international conference on Computer-aided design
Test Generation for Mixed-Signal Devices Using Signal Flow Graphs
Journal of Electronic Testing: Theory and Applications
7.2 Enhancing Test Effectiveness for Analog Circuits Using Synthesized Measurements
VTS '98 Proceedings of the 16th IEEE VLSI Test Symposium
VTS '99 Proceedings of the 1999 17TH IEEE VLSI Test Symposium
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In our previous work we elaborated a multifrequency test generation method (TPG) for detecting parametric and catastrophic faults in linear analog circuits. The method was formulated as an optimization problem which was solved by Sequential Quadratic Programming (SQP), a non-linear programming method available in MATLAB. Such standard optimization methods are based on and process local information and consequently cannot guarantee a global optimum. In this paper we propose a method based on Constraint Logic Programming(CLP) that solves the optimization problem in TPG as a series of Constraint Satisfaction Problems (UPS). Our TPG method is fully automatic and provides tight and guaranteed bounds on the global optima of a nonlinear function. The TPG method was implemented in CLP(BNR) Prolog. First, we illustrate the effectiveness of our approach on a number of nonlinearfunctions known to be dificult, and then we apply it to a realistic electronic circuit in the context of TPG. The two methods produce same results except for one case where S&P falls into a local minimum. This could lead to a wrong test selection. Moreover while the TPG took over a week of work using SQP it was solved in a matter of minutes using CLP.