High-Power-Efficiency Readout Circuit Employing Average Capacitance-to-Voltage Converter for Micro-Electro-Mechanical System Capacitive Accelerometers.

A capacitance-to-voltage converter (CVC) is proposed in this paper and applied to a readout circuit for a micro-electro-mechanical system (MEMS) accelerometer to improve the power efficiency. In a traditional readout circuit, the front-end CVC has to operate at a high sampling frequency to resist thermal noise deterioration due to the large parasitic capacitance introduced by the mechanical sensing element. Thus, the back-end analog-to-digital converter (ADC) also has to operate at a high sampling frequency to avoid noise aliasing when sampling the output signal of the CVC, which leads to high power consumption. The average CVC technique is proposed in this paper to reduce the sampling frequency requirement of the back-end ADC and thus reduce the power consumption. Both the traditional readout circuit and the proposed readout circuit are simulated with a commercial 0.18 µm BCD process. The simulation results show that noise aliasing occurs, and the noise power spectral density (PSD) of the traditional readout circuit increases by 12 dB when the sampling frequency of back-end ADC is reduced by 24 dB. However, in the proposed readout circuit, a noise aliasing effect does not occur. Moreover, the proposed readout circuit reduces the power consumption by 53% without thermal noise deterioration. In addition, the proposed CVC circuits are fabricated in an 0.18 µm BCD process, and the test results show that the presented readout circuit based on the average CVC technique can obtain better performance than the traditional CVC-based readout circuit.

MPCNet: Compressed multi-view video restoration via motion-parallax complementation network.

The performance in restoring compressed multi-view video (MVV) of the existing learning-based methods is limited because they only utilize information of temporally adjacent frames or parallax neighboring views. However, the compression artifacts caused by multi-view coding (MVC) may be related to the reference errors of intra-frame, inter-frame, and inter-view. In this paper, with delicately utilizing the stereo information from both temporal and parallax domains, a motion-parallax complementation network (MPCNet) is proposed to restore the quality of compressed MVV more efficiently. First, we introduce a motion-parallax complementation strategy consisting of a coarse stage and a fine stage. By mutually compensating the feature extracted from multiple domains, useful multi-frame information can be efficiently preserved and aggregated step by step. Second, an attention-based feature filtering and modulation module (AFFM) is proposed, which provides an efficient fusion method for two features by suppressing misleading information. By deploying it in most submodules of the proposed approach, the representational ability of MPCNet can be improved, resulting in a more substantial restoration performance. Experimental results prove the effectiveness of MPCNet by an average increase of 1.978 dB in PSNR, and 0.0282 in MS-SSIM. The BD-rate reduction can reach 47.342% on average. The subjective quality is greatly improved and lots of compression distortions are eliminated. Meanwhile, this work also benefits the accuracy improvement for high-level vision tasks, e.g., mIoU of semantic segmentation and mAP of object detection achieve 0.352 and 51.71, respectively. Quantitative and qualitative analyses demonstrate that MPCNet outperforms state-of-the-art approaches.

Analogous plasmon-induced absorption based on an end-coupled MDM structure with area-cost-free cavities.

We theoretically investigate an end-coupled metal-dielectric-metal (MDM) structure that achieves analogous plasmon-induced absorption (APIA) in an area-cost-free manner. First, a squared ring is set to end-couple with MDM input and output waveguides, generating three Lorentzian-like peaks in the spectrum. Then, two APIA windows as well as two Fano resonances can be induced via appropriately arranging two area-free cavities. Numerous numerical results demonstrate that the proposed structure has remarkable sensing and phase characteristics. Our proposed PIA-based MDM structure is promising in potential applications of bio-chemical sensing, slow light devices, optical switching, and chip-scale plasmonic devices.