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Creators/Authors contains: "Tang, Wei"

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  1. ; ; ( , Proceedings of the 23th ACM Conference on Economics and Computation)
    Free, publicly-accessible full text available July 12, 2023
  2. ; ; ; ; ( , IEEE Sensors Journal)
    Free, publicly-accessible full text available June 20, 2023
  3. ; ; ; ; ; ; ; ; ; ; et al ( , Nature)
    Free, publicly-accessible full text available April 21, 2023
  4. ; ; ( , 35th Conference on Neural Information Processing Systems (NeurIPS 2021))
    Free, publicly-accessible full text available December 4, 2022
  5. ; ( , IEEE Transactions on Biomedical Circuits and Systems)
    Free, publicly-accessible full text available October 1, 2022
  6. ; ; ; ; ; ( , 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS))
    Free, publicly-accessible full text available September 27, 2022
  7. ; ; ; ( , IEEE Transactions on Circuits and Systems I: Regular Papers)
    This paper presents a ternary low-density parity-check (LDPC) error correction system for wireless electrocardiogram sensors to improve the accuracy of arrhythmia classification. The classification system is based on ternary Delta-modulated bitstreams and rotation linear kernel support vector machines, which identifies the supraventricular ectopic beat (SVEB) and the ventricular ectopic beat (VEB) over the normal heartbeats. We model errors using a ternary symmetric channel with probability parameter p and construct a variety of ternary LDPC codes with different coding rates by concatenating two-component sub-matrices to form a parity-check matrix with a quasi-cyclic structure that facilitates the hardware design. In particular, amore »hardware-friendly LDPC encoder circuit is proposed that leverages the highly structured parity-check matrix to perform serial generation of the parity symbols using an accumulator and a look-up table. The encoder circuits are implemented on FPGA and synthesized on ASIC using a 32 nm CMOS process. Simulation results show that the ternary LDPC codes can significantly improve classification accuracy in the presence of errors. For example, with an error probability of up to 21% in the sensor output bitstreams, the classification accuracy remains above 99% with the proposed error correction system.« less
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  8. ; ( , Sensors)
    This paper presents a wearable motion tracking system with recording and playback features. This system has been designed for gait analysis and interlimb coordination studies. It can be implemented to help reduce fall risk and to retrain gait in a rehabilitation setting. Our system consists of ten custom wearable straps, a receiver, and a central computer. Comparing with similar existing solutions, the proposed system is affordable and convenient, which can be used in both indoor and outdoor settings. In the experiment, the system calculates five gait parameters and has the potential to identify deviant gait patterns. The system can trackmore »upper body parameters such as arm swing, which has potential in the study of pathological gaits and the coordination of the limbs.« less
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  9. ; ; ( , Proceedings of The 24th International Conference on Artificial Intelligence and Statistics)
    Accepted Manuscript Full Text Available
  10. ; ; ; ; ( , Proceedings of the 26th ACM International Conference on Architectural Support for Programming Languages and Operating Systems)
    Quantum computing (QC) is a new paradigm offering the potential of exponential speedups over classical computing for certain computational problems. Each additional qubit doubles the size of the computational state space available to a QC algorithm. This exponential scaling underlies QC’s power, but today’s Noisy Intermediate-Scale Quantum (NISQ) devices face significant engineering challenges in scalability. The set of quantum circuits that can be reliably run on NISQ devices is limited by their noisy operations and low qubit counts. This paper introduces CutQC, a scalable hybrid computing approach that combines classical computers and quantum computers to enable evaluation of quantum circuitsmore »that cannot be run on classical or quantum computers alone. CutQC cuts large quantum circuits into smaller subcircuits, allowing them to be executed on smaller quantum devices. Classical postprocessing can then reconstruct the output of the original circuit. This approach offers significant runtime speedup compared with the only viable current alternative -- purely classical simulations -- and demonstrates evaluation of quantum circuits that are larger than the limit of QC or classical simulation. Furthermore, in real-system runs, CutQC achieves much higher quantum circuit evaluation fidelity using small prototype quantum computers than the state-of-the-art large NISQ devices achieve. Overall, this hybrid approach allows users to leverage classical and quantum computing resources to evaluate quantum programs far beyond the reach of either one alone.« less
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