We report systems for network measurements at millimeter-wave frequencies. Active probes are used for on-wafer measurements to approximately 150 GHz. The active probes incorporate monolithic GaAs mm-wave network analysis circuits (comprising a nonlinear transmission line stimulus signal generator and a directional sampling circuit) and lowloss, rugged quartz coplanar-waveguide probe tips. Wideb...

A new neural network approach is proposed to solve the blind signal separation problem under both nonlinear and overcomplete conditions. To our knowledge, most previous algorithms including FOCal Underdetermined System Solver (FOCUSS) focus on linear distortion which may not accord with practical applications. We base our work on the FOCUSS algorithm but develop it further to apply for nonlinea...

The models described in this paper for treating congestion in DEA are extended by according them chance constrained programming formulations. The usual route used in chance constrained programming is followed here by replacing these stochastic models with their ‘‘deterministic equivalents.’’ This leads to a class of non-linear problems. However, it is shown to be possible to avoid some of the n...

This paper introduces a new decentralized adaptive neural network controller for a class of large-scale nonlinear systems with unknown non-affine subsystems and unknown interconnections represented by nonlinear functions. A multilayer feedforward neural network is used to represent the controller’s structure. The ultimate boundedness of the closed loop system is guaranteed through Lyapunov stab...

estimating the final price of products is of great importance. for manufacturing companies proposing a final price is only possible after the design process over. these companies propose an approximate initial price of the required products to the customers for which some of time and money is required. here using the existing data of already designed transformers and utilizing the bayesian anal...

With the purpose of analyzing non-stationary time series, this paper innovates the nonlinear cointegration discriminate analysis by introducing support vector machine and innovated feature-weighting model to overcome existing limitations of two methods, that is, the statistical approach and the neural network used by the nonlinear cointegration theory. Then, the application of the innovated met...

In achieving accurate results, current nonlinear elastic recovery applications of finite element (FE) analysis have become more complicated for sheet metal springback prediction. In this paper, an artificial neural network (ANN) was used to mimic the nonlinear elastic recovery and provides a generalized solution in the FE analysis. The nonlinear elastic recovery was processed through back-propa...