Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: The analog/RF functional test which is based on specification circuit testing is very costly due to lengthy test times and highly sophisticated test equipment. Alternative test measures, extracted by means of Built-in Self Test (BIST) techniques, are a promising approach to replace standard specification-based tests. Hover, these test measures must be evaluated at the design stage by estimating the Test Escapes (T e ) and the Yield Loss (Y l ). An accurate estimation of these metrics requires a large non-biased sample of circuit instances including parametric defective ones. A necessary number of these circuits cannot be obtained with a Monte Carlo simulation alone. Statistical learning techniques, in combination with Monte Carlo simulation, can allow the generation of such a sample for multivariate test metrics estimation. The development of Extreme Value Theory (EVT) has provided a rigorous tool for the computation of parametric test metrics. Hover, this theory is very complex and difficult to apply in the case of multivariate problems. ,  propose an improvement of this approach. The classification of the circuits is based on the specifications and the test limits instead of the extreme thresholds and no post-classification simulation is necessary. Also,  illustrate the use of this model for the evaluation of a filter BIST technique.
['Ahcène Bounceur', 'Belkacem Brahmi', 'Kamel Beznia', 'Reinhardt Euler']
I am writing a research paper on a idea Accurate analog/RF BIST evaluation based on SVM classification of the process parameters
[{"from": "human", "value": "I am writing a research paper on a idea Accurate analog/RF BIST evaluation based on SVM classification of the process parameters"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: The analog/RF functional test which is based on specification circuit testing is very costly due to lengthy test times and highly sophisticated test equipment. Alternative test measures, extracted by means of Built-in Self Test (BIST) techniques, are a promising approach to replace standard specification-based tests. Hover, these test measures must be evaluated at the design stage by estimating the Test Escapes (T e ) and the Yield Loss (Y l ). An accurate estimation of these metrics requires a large non-biased sample of circuit instances including parametric defective ones. A necessary number of these circuits cannot be obtained with a Monte Carlo simulation alone. Statistical learning techniques, in combination with Monte Carlo simulation, can allow the generation of such a sample for multivariate test metrics estimation. The development of Extreme Value Theory (EVT) has provided a rigorous tool for the computation of parametric test metrics. Hover, this theory is very complex and difficult to apply in the case of multivariate problems. ,  propose an improvement of this approach. The classification of the circuits is based on the specifications and the test limits instead of the extreme thresholds and no post-classification simulation is necessary. Also,  illustrate the use of this model for the evaluation of a filter BIST technique."}]