Exact calculation of the Hessian matrix for the multilayer perceptron
Neural Computation
Computer-Aided Analysis of Electronic Circuits: Algorithms and Computational Techniques
Computer-Aided Analysis of Electronic Circuits: Algorithms and Computational Techniques
A Signal-Flow-Graph Approach to On-line Gradient Calculation
Neural Computation
Some invariant sums of higher-order sensitivities
International Journal of Circuit Theory and Applications
Analog circuit design by nonconvex polynomial optimization: Two design examples
International Journal of Circuit Theory and Applications
A method for fast simulation of multiple catastrophic faults in analogue circuits
International Journal of Circuit Theory and Applications
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This paper presents the application of signal flow graphs (SFG) in the calculation of higher-order derivatives (sensitivities) of the linear circuit functions. The idea of exact differentiation of the circuit functions is based on the adjoint networks, translated into SFG language. Thanks to its application, it is possible to calculate the exact value of any order derivative of circuit function without knowing this function in explicit form. Moreover, these derivatives can be determined on the basis of analysis of only two graphs (circuits): the original and adjoint one. We show that the SFG approach to the sensitivity calculation allows to reduce greatly the complexity of calculations. Copyright © 2011 John Wiley & Sons, Ltd. (The paper ‘Higher order differentiation of network functions using signal flow graphs’ of S. Osowski presents the rules of the exact differentiation of linear network functions by using the signal flow graph (SFG). It was shown that by defining adjoint SFG (ASFG) based on the adjoint network theory (see Figure 1) any order derivatives of the network functions can be determined through the analysis of only two graphs (SFG and ASFG) at different unity excitations. This method simplifies sensitivity analysis significantly.)