实时硬件系统中控制方法的研究

由于实时硬件系统的规模和复杂度不断增大，系统结构的模块化设计已成为硬件系统开发的发展趋势。研究了硬件系统中模块控制的方法和特点。结合MPEG2电视编码器中各功能模块的特点，提出了适合该硬件系统的模块控制方案，说明了控制模块的硬件设计思想和软件实现。实践证明，该方案满足系统实时性和可靠性的设计要求。     

Grouped Approach for the Design of H.264/AVC Motion Estimation Architectures

This letter presents a novel approach for organizing computational resources into groups within H.264/AVC motion estimation architectures, leading to reductions of up to 75% in the equivalent gate count with respect to state‐of‐the‐art designs.     

CPLD在雷达伺服轴角编码电路中的应用

介绍一种针对正、余弦旋转变压器—数字转换器(RDC)模块，用复杂可编程逻辑器件(CPLD)技术实现伺服轴角编码电路设计的方案。分析了轴角编码器系统中14XSZ系列旋转变压器—数字转换器的原理、轴角粗精组合原理及轴角纠错原理。详细介绍了CPLD的内部功能电路、CPLD轴角粗精组合和纠错实现电路，以及CPLD的工作时序图。提出了利用CPLD实现轴角粗精组合处理的方案，并通过了实际系统运行的考验，证明该方案可行。     

利用弧形光栅尺测量大型转轴扭矩的原理研究

利用弧形光栅尺的旋转微位移测量功能,组建一组测量体系,用于测量巨型转轴的扭矩。采用四组相同的弧形光栅尺同时测量两截面的相对转角,通过多点测量实现误差均化,得出了消除转轴直径对测量影响的公式,使仪器的环境适应能力得到了极大地提高。根据不同的工作情况,提出了相应的动态测量扭矩的计算方程。实现了大型机械设备主传动的动力监测,为设备自动化、智能化奠定了基础。     

基于HOP的可调光编码／解码器的研究

提出了一种基于全息光处理器的可调光编码/解码器的实现方案。全息光处理器可以在空间进行编/解码，每个通信网络单元可以采用任意速率的数字或模拟的调制信号，它非常适合于多媒体的通信网络环境，通过对全息光处理器的折射率大小和位置的控制，当一个输入光脉冲经过光处理器中具有特定折射率的空间位置后，便可在处理器的输出端口得到合适的输出信号。本文给出了这种基于全息光处理器的可调光编码/解码器的仿真实验，结果是可行的，与以前文献中提出的结构相比，减小了硬件实现的复杂性，降低了成本和功耗，便于集成。     

基于SPCE061A单片机的髋作用力测试仪设计

介绍了基于SPCE061A单片机的髋作用力测试仪的系统结构及部分软件编写流程,着重分析了测试仪的测力方法以及使用光电编码器进行测速和鉴相的原理.测试仪以SPCE061A单片机为控制核心,配有串行通信口,具备上位机实时监控、数据保存和复现、测试数据离线分析等功能.实验证明,该测试仪具有测量准确、稳定性高及操控界面友好等优点.     

Selective body biasing for post-silicon tuning of sub-threshold designs: A semi-infinite programming approach with Incremental Hypercubic Sampling

Sub-threshold designs have become a popular option in many energy constrained applications. However, a major bottleneck for these designs is the challenge in attaining timing closure. Most of the paths in sub-threshold designs can become critical paths due to the purely random process variation on threshold voltage, which exponentially impacts the gate delay. In order to address timing violations caused by process variation, post-silicon tuning is widely used through body biasing technology, which incurs heavy power and area overhead. Therefore, it is imperative to select only a small group of the gates with body biasing for post-silicon-tuning. In this paper, we first formulate this problem as a linear semi-infinite programming (LSIP). Then an efficient algorithm based on the novel concept of Incremental Hypercubic Sampling (IHCS), specially tailored to the problem structure, is proposed along with the convergence analysis. Compared with the state-of-the-art approach based on adaptive filtering, experimental results on industrial designs using 65 nm sub-threshold library demonstrate that our proposed IHCS approach can improve the pass rate by up to 7.3× with a speed up to 4.1×, using the same number of body biasing gates with about the same power consumption.     

Adaptive visual target detection and tracking using weakly supervised incremental appearance learning and RGM-PHD tracker

Multiple visual target tracking is a challenging problem due to various uncertainties including occlusion, miss-detection and noisy measurement. Most tracking approaches utilize an object-specific detector, pre-trained on many labeled images, to provide suitable measurements for their tracking system. In this paper, we use a simple background subtraction detector which only needs the background image to localize targets independent of their shape or type. In order to cope with the uncertainties resulted by the detector, we propose an adaptive appearance model and develop an incremental appearance learning algorithm to learn the target appearances in time. The proposed method employs the background information and our defined keypoints’ miss-matched history to adapt the target appearances within different frames. Furthermore, we combine Refined Gaussian Mixture Probability Hypothesis Density (RGM-PHD) tracker with the detectors to keep target trajectories and handle uncertainties. The experiments conducted on several video datasets show the effectiveness of our proposed method.     

Korean automatic spacing using pretrained transformer encoder and analysis

Automatic spacing in Korean is used to correct spacing units in a given input sentence. The demand for automatic spacing has been increasing owing to frequent incorrect spacing in recent media, such as the Internet and mobile networks. Therefore, herein, we propose a transformer encoder that reads a sentence bidirectionally and can be pretrained using an out-of-task corpus. Notably, our model exhibited the highest character accuracy (98.42%) among the existing automatic spacing models for Korean. We experimentally validated the effectiveness of bidirectional encoding and pretraining for automatic spacing in Korean. Moreover, we conclude that pretraining is more important than fine-tuning and data size.