No abstract

This paper studies the effects of the covering layers on the performance of a cross-like Hall plate. Three different structures of a cross-like Hall plate in various sizes are designed and analyzed. The Hall plate sensitivity and offset are characterized using a self-built measurement system. The effect of the P-type region over the active area on the current-related sensitivity is studied for different Hall plate designs. In addition, the correlation between the P-type covering layer and offset is analyzed. The best structure out of three designs is determined. Besides, a modified eight-resistor circuit model for the Hall plate is presented with improved accuracy by taking the offset into account.

Deep learning algorithms' powerful capabilities for extracting useful latent information give them the potential to outperform traditional financial models in solving problems of the stock market which is a complex system. In this paper, we explore the use of advanced deep learning algorithms for stock-index tracking. We partially replicate the CSI 300 Index by optimizing with respect to the difference between the returns of the tracking portfolio and the target index. We extract the complex non-linear relationship between index constituents and select a subset of constituents to construct a dynamic tracking portfolio by six well-known auto-encoders (single-hidden-layer undercomplete, sparse, contractive, stacked, denoising, and variational auto-encoders) that have been widely used in contexts other than stock-index tracking. Empirical results show that the auto-encoder-based strategies perform better than conventional ones when the tracking portfolio is constructed with a small number of stocks. Furthermore, strategies based on auto-encoders capable of learning high-capacity encodings of the input, such as sparse and denoising auto-encoders, have even better tracking performance. Our findings offer evidence that deep learning algorithms with explicitly designed hierarchical architectures are suitable for index tracking problems.

This work studies the effects of an aluminum covering on the performance of cross-like Hall devices. Four different Hall sensor structures of various sizes were designed and fabricated. The sensitivity and offset of the Hall sensors, two key points impacting their performance, were characterized using a self-built measurement system. The work analyzes the influences of the aluminum covering on those two aspects of the performance. The aluminum layer covering mainly leads to an eddy-current effect in an unstable magnetic field and an additional depletion region above the active region. Those two points have influences on the sensitivity and the offset voltage, respectively. The analysis guides the designer whether to choose covering with an aluminum layer the active region of the Hall sensor as a method to reduce the flicker noise and to improve the stability of the Hall sensor. Because Hall devices, as a reference element, always suffer from a large dispersion, improving their stability is a crucial issue.

In this paper, a new single-device three-dimensional (3D) Hall sensor called a cross-shaped 3D Hall device is designed based on the five-contact vertical Hall device. Some of the device parameters are based on 0.18 μm BCDliteTM technology provided by GLOBALFOUNDRIES. Two-dimensional (2D) and 3D finite element models implemented in COMSOL are applied to understand the device behavior under a constant magnetic field. Besides this, the influence of the sensing contacts, active region’s depth, and P-type layers are taken into account by analyzing the distribution of the voltage along the top edge and the current density inside the devices. Due to the short-circuiting effect, the sensing contacts lead to degradation in sensitivities. The P-type layers and a deeper active region in turn are responsible for the improvement of sensitivities. To distinguish the P-type layer from the active region which plays the dominant role in reducing the short-circuiting effect, the current-related sensitivity of the top edge (Stop) is defined. It is found that the short-circuiting effect fades as the depth of the active region grows. Despite the P-type layers, the behavior changes a little. When the depth of the active region is 7 μm and the thickness of the P-type layers is 3 μm, the sensitivities in the x, y, and z directions can reach 91.70 V/AT, 92.36 V/AT, and 87.10 V/AT, respectively.