An efficient neural network approach for nanoscale FinFET modelling and circuit simulation

The present paper demonstrates the suitability of artificial neural network (ANN) for modelling of a FinFET in nano-circuit simulation. The FinFET used in this work is designed using careful engineering of source-drain extension, which simultaneously improves maximum frequency of oscillation f(max) because of lower gate to drain capacitance, and intrinsic gain A(V0) = g(m)/g(ds), due to lower output conductance g(ds). The framework for the ANN-based FinFET model is a common source equivalent circuit, where the dependence of intrinsic capacitances, resistances and dc drain current I-d on drain-source V-ds and gate-source V-gs is derived by a simple two-layered neural network architecture. All extrinsic components of the FinFET model are treated as bias independent. The model was implemented in a circuit simulator and verified by its ability to generate accurate response to excitations not used during training. The model was used to design a low-noise amplifier. At low power (J(ds) similar to 10 mu A/mu m) improvement was observed in both third-order-intercept IIP3 (similar to 10 dBm) and intrinsic gain A(V0) (similar to 20 dB), compared to a comparable bulk MOSFET with similar effective channel length. This is attributed to higher ratio of first-order to third-order derivative of I-d with respect to gate voltage and lower g(ds), in FinFET compared to bulk MOSFET. Copyright (C) 2009 John Wiley & Sons, Ltd.

Improved Nonlinear PCA for Process Monitoring Using Support Vector Data Description

Nonlinear principal component analysis (PCA) based on neural networks has drawn significant attention as a monitoring tool for complex nonlinear processes, but there remains a difficulty with determining the optimal network topology. This paper exploits the advantages of the Fast Recursive Algorithm, where the number of nodes, the location of centres, and the weights between the hidden layer and the output layer can be identified simultaneously for the radial basis function (RBF) networks. The topology problem for the nonlinear PCA based on neural networks can thus be solved. Another problem with nonlinear PCA is that the derived nonlinear scores may not be statistically independent or follow a simple parametric distribution. This hinders its applications in process monitoring since the simplicity of applying predetermined probability distribution functions is lost. This paper proposes the use of a support vector data description and shows that transforming the nonlinear principal components into a feature space allows a simple statistical inference. Results from both simulated and industrial data confirm the efficacy of the proposed method for solving nonlinear principal component problems, compared with linear PCA and kernel PCA.

Millimeter-wave printed circuit board characterization using substrate integrated waveguide resonators

This paper proposes a substrate integrated waveguide
(SIW) cavity-based method that is compliant with
ground-signal–ground (GSG) probing technology for dielectric
characterization of printed circuit board materials at millimeter
wavelengths. This paper presents the theory necessary to retrieve
dielectric parameters from the resonant characteristics of SIW
cavities with particular attention placed on the coupling scheme
and means for obtaining the unloaded resonant frequency. Different
sets of samples are designed and measured to address the
influence of the manufacturing process on the method. Material
parameters are extracted at - and -band from measured data
with the effect of surface roughness of the circuit metallization
taken into account.

Electronic Circuit Packages

This invention relates to electronic circuit packages designed to hold high frequency circuits operating particularly, but not exclusively, in the microwave, millimeter wave, and sub-millimeter wave bands. The invention provides a package incorporating a cavity in a material for containment of the circuits, wherein the package further incorporates at least one conductive surface mounted on an inner surface extending into the cavity, the conductivity thereof being adapted to be at least partially absorbent to electromagnetic radiation. The conductive surface according to the present invention will tend to attenuate electromagnetic radiation present within the cavity, and so help to prevent undesired coupling from one point to another within the cavity. The conductivity of the conductive material is preferably arranged to match the impedance of the radiation mode estimated or computed to be present within the cavity.