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188 results on '"Sun, Kaixuan"'

14. A Soft-Aided Staircase Decoder Using Three-Level Channel Reliabilities

Author

Lei, Yi, Chen, Bin, Liga, Gabriele, Balatsoukas-Stimming, Alexios, Sun, Kaixuan, and Alvarado, Alex

Subjects
Computer Science - Information Theory, Electrical Engineering and Systems Science - Signal Processing
Abstract

The soft-aided bit-marking (SABM) algorithm is based on the idea of marking bits as highly reliable bits (HRBs), highly unreliable bits (HUBs), and uncertain bits to improve the performance of hard-decision (HD) decoders. The HRBs and HUBs are used to assist the HD decoders to prevent miscorrections and to decode those originally uncorrectable cases via bit flipping (BF), respectively. In this paper, an improved SABM algorithm (called iSABM) is proposed for staircase codes (SCCs). Similar to the SABM, iSABM marks bits with the help of channel reliabilities, i.e., using the absolute values of the log-likelihood ratios. The improvements offered by iSABM include: (i) HUBs being classified using a reliability threshold, (ii) BF randomly selecting HUBs, and (iii) soft-aided decoding over multiple SCC blocks. The decoding complexity of iSABM is comparable of that of SABM. This is due to the fact that on the one hand no sorting is required (lower complexity) because of the use of a threshold for HUBs, while on the other hand multiple SCC blocks use soft information (higher complexity). Additional gains of up to 0.53 dB with respect to SABM and 0.91 dB with respect to standard SCC decoding at a bit error rate of $10^{-6}$ are reported. Furthermore, it is shown that using 1-bit reliability marking, i.e., only having HRBs and HUBs, only causes a gain penalty of up to 0.25 dB with a significantly reduced memory requirement.

Published
2021
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25. Highly crystalline graphite nanofibers as an anode for high-performance potassium-ion batteries.

Author

Sun, Kaixuan, Chang, Kun, Tan, Jinshuo, Sun, Chuan-Fu, and Liu, Qin

Subjects
*GRAPHITE, *ELECTRON diffusion, *PRUSSIAN blue, *CHARGE exchange, *ANODES, *ENERGY consumption, *NANOFIBERS
Abstract

Graphite is considered the most promising anode for low-cost potassium-ion batteries (PIBs). However, the large volume change and sluggish kinetics due to the large ionic size of K+ cause inferior rate capability and poor cycling stability for the graphite anode. Herein, we report highly crystalline graphite nanofibers (GNFs) as an anode material for PIBs, which deliver flat voltage plateaus with a high specific capacity of 257 mA h g−1. The highly graphitized, fiber-shaped nanostructure not only mitigates the volume expansion caused by K+-intercalation but also facilitates both ionic diffusion and electron transfer. GNFs achieve a long cycle life of 1 year with 99% capacity retention and fast K+-intercalation kinetics. Moreover, the low-defect structure of GNFs ensures a high initial coulombic efficiency of up to 74.23%. A potassium-ion full-cell prototype featuring GNFs anode and Prussian blue analogue cathode demonstrates a high energy efficiency of up to 90.6%. This low-defect graphitic nanofiber may offer insights into the design of carbon-based anodes for PIBs. [ABSTRACT FROM AUTHOR]

Published
2024
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34. An Approach to Data Modeling via Temporal and Spatial Alignment.

Author

Zhang, Dapeng, Sun, Kaixuan, and Zhang, Shumei

Subjects
DATA modeling, TIME series analysis
Abstract

It is important for data modeling to comply with a data observation window of physical variables behind the data. In this paper, a multivariate data alignment method is proposed to follow different time scales and different role effects. First, the length of the sliding windows is determined by the frequency characteristics of the time-series reconstruction. Then, the time series is aligned to the length of the window by a sequence-to-sequence neural network. This neural network is trained by replacing the loss function with dynamic time warping (DTW) in order to prevent the losses of the time series. Finally, the attention mechanism is introduced to adjust the effect of different variables, which ensures that the data model of the matrix is in accord with the intrinsic relation of the actual system. The effectiveness of the approach is demonstrated and validated by the Tennessee Eastman (TE) model. [ABSTRACT FROM AUTHOR]

Published
2024
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