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Source publication
A neural network approach is proposed for the characterization of
twisted wire bundles multiconductor transmission lines. The neural
network is suitably trained with few cross section configurations to
learn the behavior of the per unit length parameters of the nonuniform
bundle. The procedure allows a fast characterization of the nonuniform
bundle...
Contexts in source publication
Context 1
... a first example, a simple MTL with the cross section shown in Fig. 1 has been considered. It consists of three wires with a double dielectric coating each and an overall dielectric insulation. The conductor radius is mm. The radius of the dielectric coatings are mm, mm, mm, and mm. The wire's centers coordinates of the initial cross-section configuration are , , and . The MTL height above the ground ...
Context 2
... mm, mm, mm, and mm. The wire's centers coordinates of the initial cross-section configuration are , , and . The MTL height above the ground plane is mm. The three wires maintain the same relative position along the entire MTL. The nonuniform bundle is generated by a rotation of the wires around the bundle axis of an angle between 0 and 120 (see Fig. ...
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Citations
... The impedance mismatches found along the power electric network provoke intense multipath fading in the area of MHz [1][2][3][4][5][6][7][8][9]. Due to structural peculiarities, certain types of triple-pole (phase-neutralground) cables follow the two-conductor uniform TL model [10][11][12][13][14][15][16], whereas most tricels, as well as any multi-phase (two-phase, three-phase) cable, require a multiconductor transmission line (MTL) model [17][18][19][20][21][22][23][24][25][26][27]. Therefore, a computationally realisable travelling-wave analysis of MTL networks enabling in particular simulation of Power-Line Communication (PLC) channels in the Time Domain (TD) would be of considerable contribution. ...
In Part I of this work, analysis of uniform multi-conductor transmission line networks is performed on travelling-wave basis, via "quasi-TEM" approach. Narrowband interpretation of the modal theory in the time domain and quantification of the multiple reflections effect are both included. Theoretical demonstration and analytical formulation are provided, along with guidelines towards computational implementation. Any network formed of lossy, diagonalisable uniform multi-conductor transmission lines of either distinct or degenerate eigenvalues is covered. This work applies especially in the field of Power-Line Communications, as High-Frequency transmission over the power electric network is dominated by multipath propagation.
A neural network based procedure is proposed for the crosstalk prediction in twisted bundles. The nonuniform bundle is approximated as a cascade of uniform sections and the neural network is suitably trained with few cross section configurations to learn the behavior of the per unit length parameters. The procedure allows a fast and accurate prediction tool.
