Abstract. The applications of Total Variation (TV) algorithms for Electrical Impedance Tomography (EIT) have been investigated. The use of the TV regularisation technique helps to preserve discontinuities in reconstruction, such as the boundaries of perturbations and sharp changes in conductivity, which are unintentionally smoothed by traditional 2 l norm regularisation. However, the non-differentiability of TV regularisation has led to the use of different algorithms. Recent advances in TV algorithms such as Primal Dual Interior Point Method (PDIPM), Linearised Alternating Direction Method of Multipliers (LADMM) and Spilt Bregman (SB) method have all been demonstrated successfully for EIT applications, but no direct comparison of the techniques has been made. Their noise performance, spatial resolution and convergence rate applied to time difference EIT were studied in simulations on 2D cylindrical meshes with different noise levels, 2D cylindrical tank and 3D anatomically head-shaped phantoms containing vegetable material with complex conductivity. LADMM had the fastest calculation speed but worst resolution due to the exclusion of the second-derivative; PDIPM reconstructed the sharpest change in conductivity but with lower contrast; SB had a faster convergence rate than PDIPM and the lowest image error.
Electric field-induced resistive switching (RS) and related effects are studied for the ZnO-based device Ag/AgO x /Mg 0.2 Zn 0.8 O/Pt. The system exhibits a bipolar resistive switching (BRS) for the current (I)-voltage (V) cycles, with the set/reset voltage distributing in a narrow region around 0.15 V/0.16 V. The high to low resistance ratio is ∼10, and the resistive state is well retainable. However, the RS becomes unipolar (unipolar resistive switching-URS) when electric pulses are applied, with a fairly wide distribution of the set/reset voltages, though the resistive state is still well retainable. It was further found that a backward transition from the URS to the BRS state can be occasionally triggered by simply performing I-V cycling in the negative branch, which shows the strong competition of the BRS and URS states. Both the BRS and URS states were stable and reproducible over 90 cycles. Possible mechanisms for the BRS and URS state and their mutual transition were discussed.
The memristor has broad application prospects in many fields, while in many cases, those fields require accurate impedance control. The nonlinear model is of great importance for realizing memristance control accurately, but the implementing complexity caused by iteration has limited the actual application of this model. Considering the approximate linear characteristics at the middle region of the memristance-charge (M-q) curve of the nonlinear model, this paper proposes a memristance controlling approach, which is achieved by linearizing the middle region of the M-q curve of the nonlinear memristor, and establishes the linear relationship between memristances M and input excitations so that it can realize impedance control precisely by only adjusting input signals briefly. First, it analyzes the feasibility for linearizing the middle part of the M-q curve of the memristor with a nonlinear model from the qualitative perspective. Then, the linearization equations of the middle region of the M-q curve is constructed by using the shift method, and under a sinusoidal excitation case, the analytical relation between the memristance M and the charge time t is derived through the Taylor series expansions. At last, the performance of the proposed approach is demonstrated, including the linearizing capability for the middle part of the M-q curve of the nonlinear model memristor, the controlling ability for memristance M, and the influence of input excitation on linearization errors.
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