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Neural network models extended to higher-dimensional numbers have been studied in recent years. In particular, quaternions have an advantage with respect to the expression of rotation in a three-dimensional space. On the other hand, the problem that estimates the cause of an observed result is called an inverse problem, whose solutions have been studied in various engineering fields. In this study,...
An artificial neural network approach for the automated design of a positive type second generation current conveyor is presented in this paper. A multi-layer perceptron structure is successfully employed to estimate the corresponding transistor dimensions for a given set of desired performance criteria of the circuit. Data generated by a circuit simulation program (SPICE) is used to train the artificial...
Neural Network methods for stock market prediction have received attention in the literature. However, the methods that form the current state of the art have generally been unable to demonstrate sustained profitability over a significant period of time. The authors of this paper show, through the application of over ten years of experience in Quantitative Modelling and Trading, a proof of concept...
In this brief, the problem of sampled-data state estimation for static neural network is investigated. The statefeedback control design method we develop in this paper relies on the information from the sampled states. By constructing a class of Lyapunov function and combining with some inequality, a sufficient condition for the existence of state estimator is derived.
Synergistic and distributed neural network models are employed in this work for Microarray data classification. The proposed approach uses subspace grids as input to synergistic and distributed neural network models. The paper first describes projection of multidimensional Microarray data to a number of lower dimensional subspaces. This work makes use of two algorithms to define lower dimensional...
The accuracy of three dimensional vision depends heavily on the accuracy of camera calibration. A major source of calibration error is the system nonlinearity due mainly to optical aberration. Although there are various physical models that have been employed to correct the nonlinear image distortion due to the aberration, it is uncertain practically that which model best fits a given optical system...
This study introduces technology independent sizing for CMOS integrated opamp based on neural networks (NN). The aim is to predict the transistor sizes of integrated opamp that correspond to design constraints, without knowing the SPICE technology parameters. Furthermore, in contrast to other modeling researches, the output specifications of integrated circuits (IC) are predicted for new technology...
The role of logistics in the construction industry is considered as a key to better performance and customer quality. This paper proposes a method to model the connection between logistics resources dedicated to a construction project and its schedule success using artificial neural networks. Schedule success can be regarded as one of the major element of customer satisfaction. Therefore a tool with...
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