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Beilstein J. Nanotechnol. 2022, 13, 444–454, doi:10.3762/bjnano.13.37
Figure 1: (a) Schematic illustration of a RBF network. (b) Schematic representation of a Gauss-neuron ensurin...
Figure 2: Transfer functions (normalized) and their main characteristics for the Gauss-neuron. (a, b) Familie...
Figure 3: (a) Amplitude of the transfer function and (b) its standard deviation from the Gaussian-like functi...
Figure 4: (a) Dynamic transfer function of a Gauss-neuron for a trapezoidal external signal for different val...
Figure 5: Sketch of the tunable kinetic inductance based on multilayer structure in the (a) closed and (b) op...
Figure 6: Spatial distribution of the pair amplitude F in the hybrid structures (a) S–FM1–s–FM2–s–FM1–s–FM2–N...
Figure 7: Kinetic inductance of the hybrid structures S–FM1–s–FM2–s–FM1–s–FM2–s–N and S–FM1–n–FM2–n–FM1–n–FM2...
Beilstein J. Nanotechnol. 2016, 7, 1397–1403, doi:10.3762/bjnano.7.130
Figure 1: (a) Principle scheme for a potential quantron. (b) Quantron flux-to-current transfer function for d...
Figure 2: Principle scheme of a three-layer perceptron conceived as layers of connected nodes (with different...
Figure 3: (a), (b) Flux-to-current characteristics of the sigma cell for different parameters of the supercon...
Figure 4: Principle scheme of an RBF neural network (where the output is a linear combination of radial basis...
Figure 5: (a), (b) Gauss cell flux-to-current transfer function for different values of the interferometer an...
Figure 6: Simulation results for the noise immunity characteristics of a G-cell based RBF ANN with (solid lin...