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Modeling of Spiking Neural Network With Optimal Hidden Layer via Spatiotemporal Orthogonal Encoding for Patterns Recognition
Zenan Huang;Yinghui Chang;Weikang Wu;Chenhui Zhao;Hongyan Luo;Shan He;Donghui Guo
IEEE Transactions on Emerging Topics in Computational Intelligence
Year: 2025 | Early Access Article |
The Spiking Neural Network (SNN) diverges from conventional rate-based network models by showcasing remarkable biological fidelity and advanced spatiotemporal computation capabilities, precisely converting input spike sequences into firing activities. This paper introduces the Spiking Optimal Neural Network (SONN), a model that integrates spiking neurons with spatiotemporal orthogonal polynomials ...Show More
Time Expansion of Pulse Echo Signal Implemented for Laser Ranging System With High Precision
Yuhang Tu;Jiang Li;Haojie Ruan;Yabin Deng;Leilei Li;Shan He;Donghui Guo
This article proposes a pulse laser ranging method based on the correlated sampling time expansion, which enhances the precision of pulse laser ranging. We introduced an additional sampling pulse signal, which has a certain frequency difference from the transmission signal. By utilizing the principle of correlation sampling, the sampling signal is used to sample the pulse echo signal, resulting in...Show More
Optimized Inference Scheme for Conditional Computation in On-Device Object Detection
Kairong Zhao;Yinghui Chang;Weikang Wu;Zirun Li;Hongyin Luo;Shan He;Donghui Guo
IEEE Embedded Systems Letters
Year: 2024 | Early Access Article |
Recently, conditional computation has been applied to on-device object detection to solve the conflict between huge computation requirments of deep neural network (DNN) and limited computation resources of edge devices. There is a need for an optimized inference scheme that can efficiently perform conditional computation in on-device object detection. This letter proposes a predictor which can pre...Show More
A Biomimetic Visual Detection Model: Event-Driven LGMDs Implemented With Fractional Spiking Neuron Circuits
Objective: Lobula giant motion detectors (LGMDs) in locusts effectively predict collisions and trigger avoidance, with potential applications in autonomous driving and UAVs. Research on LGMD characteristics splits into two views: one focusing on the presynaptic visual pathway, the other on the postsynaptic LGMD neurons. Both perspectives have support, leading to two computational models, but they ...Show More
An UVM-Based Verification Platform for Hardware and Software Co-Design
2023 IEEE 17th International Conference on Anti-counterfeiting, Security, and Identification (ASID)
Year: 2023 | Conference Paper |
As chips grow in size and complexity, functional verification in a software environment is increasingly unable to meet the needs of efficient chip production processes. Therefore, the improvement of verification efficiency becomes critical. For the bus subsystem including AXI, AHB, AXI2AHB-bridge and AHB2APB-bridge, a coverage-driven Universal Verification Methodology (UVM) hardware and software c...Show More
Optimization Algorithm Research and Design of Chip Manufacturing Virtual System Based on SECS/GEM
2023 IEEE 17th International Conference on Anti-counterfeiting, Security, and Identification (ASID)
Year: 2023 | Conference Paper |
In order to improve the production efficiency, improve the product quality and reduce the cost in the field of chip manufacturing, this paper designs a virtual system based on SECS/GEM protocol to simulate the real production process of chip manufacturing, so as to optimize each stage of chip manufacturing. The system includes a equipment-side program that simulates the equipment and a host-side p...Show More
Design of a deployable underwater robot for the recovery of autonomous underwater vehicles based on origami technique
Jisen Li;Yuliang Yang;Yumei Zhang;Hua Zhu;Yongqi Li;Qiujun Huang;Haibo Lu;Shan He;Shengquan Li;Wei Zhang;Tao Mei;Feng Wu;Aidong Zhang
2021 IEEE International Conference on Robotics and Automation (ICRA)
Year: 2021 | Conference Paper |
The recovery of autonomous underwater vehicles (AUVs) has been a challenging mission due to the limited localization accuracy and movement capability of the AUVs. To overcome these limitations, we propose a novel design of a deployable underwater robot (DUR) for the recovery mission. Utilizing the origami structure, the DUR can transform between open and closed states to maximize the performance a...Show More
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