Practical neural network recipes in C++
Practical neural network recipes in C++
Artificial Neural Networks: Theory and Applications
Artificial Neural Networks: Theory and Applications
Neural Network Training Using Genetic Algorithms
Neural Network Training Using Genetic Algorithms
ETW '03 Proceedings of the 8th IEEE European Test Workshop
CMOS Circuit Design, Layout, and Simulation, Second Edition
CMOS Circuit Design, Layout, and Simulation, Second Edition
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Characterization of semiconductor devices is used to gather as much data about the device as possible to determine weaknesses in design or trends in the manufacturing process. In this paper, we propose a novel multiple trip point characterization concept to overcome the constraint of single trip point concept in device characterization phase. In addition, we use computational intelligence techniques (e.g. neural network, fuzzy and genetic algorithm) to further manipulate these sets of multiple trip point values and tests based on semiconductor test equipments, Our experimental results demonstrate an excellent design parameter variation analysis in device characterization phase, as well as detection of a set of worst case tests that can provoke the worst case variation, while traditional approach was not capable of detecting them.