nonlinear network

nonlinear network

[′nän‚lin·ē·ər ′net‚wərk]
(electricity)
A network in which the current or voltage in any element that results from two sources of energy acting together is not equal to the sum of the currents or voltages that result from each of the sources acting alone.
References in periodicals archive ?
Using the above principle, the generalized lossy nonlinear network can be redrawn as shown in Fig.
Using the above principle, the generalized lossy nonlinear network can be redrawn as shown in Figure 3 where the current source representation has been used.
Van Esch, Accurately characterizing hard nonlinear behavior of microwave components with the nonlinear network measurement system: introducing 'nonlinear scattering functions,' Proceedings of the 5th International Workshop on Integrated Nonlinear Microwave and Millimeterwave Circuits, Duisburg, Germany, Oct.
In Chapter 2, nonlinear measurements are covered: load/source pull, vector nonlinear network analyzer and pulse measurements.
Jacobian for the nonlinear network is more complex so isn't shown.
Interestingly, in constructing proposed lossy nonlinear network we were motivated with a very interesting example of nanobioelectronics problem.
Huang, "Nonlinear network traffic prediction based on BP neural network," Journal of Computer Applications, vol.
Within a nonlinear network, the system gain, the derivative of a controlled variable to its corresponding control input, varies under different operating conditions.
Living systems are cognitive systems with an inherent tendency to structure themselves in nonlinear network patterns capable of performing highly complex functions with minimum effort.
It is capable of achieving the complex function approximation and attaining distributed representation for input data by learning a deep nonlinear network structure.
apply an unsupervised learning algorithm to learn language-independent stroke feature and combine unsupervised stroke feature learning together with automatically multilayer feature extraction to improve the representational power of text feature and develop a novel nonlinear network based on traditional Convolutional Neural Network that enables detecting multilingual text regions in the images.
A nonlinear network analyzer combined with an active multiharmonic load-pull system is described.
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