For that purpose, an experimental circuit has been designed and fabricated where open defects have been intentionally added in a set of interconnect CMOS lines.
Most biochemical studies performed on the cell-envelope to date have been focused on cataloguing individual components rather than understanding the structure as a set of interconnected physical modules (Weiner & Li, 2008).
Generally speaking, artificial neural network (ANN) can be described as a computational system consisting of a set of highly interconnected processing elements, called artificial neurons, which process information as a response to external stimuli.
Proposed scheme takes advantage of the converter structure to represent the system as a set of n interconnected subsystems, which allows to overcome the unobservable condition of the original system.
We show the pros and cons of each method and compare them on a set of large interconnect circuits, and finally point to some new research directions for this area.
A module can be defined as a set of highly interconnected, functionally-related components in a biological interaction network.
A neural network is composed of a set of highly interconnected nodes, and is a type of non-parametric regression approach for modeling complex functions [ 23, 24].
Examining structural and functional aspects of rich club organization in the human brain, our findings support and extend the idea that the rich club, a set of highly interconnected high-degree regions, is a high cost feature of brain connectivity.
The ANN, consisting of a set of highly interconnected processing units (neurons) tied together with weighted connections, includes an input layer, one or more hidden layers, and an output layer.
