Composite structure materials were potential sensing elements for magnetic sensors due to Giant magnetoimpedance (GMI) effect. Two kinds of composite wires with different magnetic/non-magnetic structures were fabricated by using electroless deposition methods and the magnetoimpedance properties were investigated. The maximum GMI ratio of 114% was acquired at 60 MHz in the composite wires with a ferromagnetic core, whereas, 116% of maximum GMI ratio was found in the composite wires with a conductive core at low frequency of 600 kHz. These results exhibit that the GMI ratio reaches the maximum when magnetoresistance ratio ∆R/R and magnetoinductance ratio ∆X/X make the comparative contributions to the total magnetoimpedance (MI). The obvious GMI effect obtained in the composite wires with conductive core frequency may provide a candidate for applications in magnetic sensors, especially at low frequencies.

Composite structure materials were potential sensing elements for magnetic sensors due to Giant magnetoimpedance (GMI) effect. Two kinds of composite wires with different magnetic/non-magnetic structures were fabricated by using electroless deposition methods and the magnetoimpedance properties were investigated. The maximum GMI ratio of 114% was acquired at 60 MHz in the composite wires with a ferromagnetic core, whereas, 116% of maximum GMI ratio was found in the composite wires with a conductive core at low frequency of 600 kHz. These results exhibit that the GMI ratio reaches the maximum when magnetoresistance ratio ΔR/R and magnetoinductance ratio ΔX/X make the comparative contributions to the total magnetoimpedance (MI). The obvious GMI effect obtained in the composite wires with conductive core frequency may provide a candidate for applications in magnetic sensors, especially at low frequencies.

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In this paper, we consider a delayed Hopfield two-neural system with a monotonic activation function and find the periodic coexistence by bifurcation analysis. Firstly, we obtain the pitchfork bifurcation of the trivial equilibrium employing the central manifold and normal form methods. The neural system exhibits two pitchfork bifurcations near the trivial equilibrium. Then, analyzing the characteristic equation of the nontrivial equilibrium, we illustrate the saddle-node bifurcation of the nontrivial equilibria. The system exhibits the multi-coexistences of the stable and unstable equilibria. Further, we illustrate the plane regions of parameters having different numbers of equilibria. To obtain a time delay in neural system dynamics, we present the stability analysis and find the periodic orbit. The system exhibits stability switching by the Hopf bifurcation curves. Finally, the dynamic behaviors near the Hopf-Hopf bifurcation point are presented. The system exhibits coexistence of multiple periodic orbits with different frequencies.

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