一个手机整句输入算法的研究与实现

随着时代的发展,手机在人们生活中起着越来越重要的作用。目前,相对于其他丰富多采的手机应用,手机输入法研究相对较少。该文针对手机存储空间小、计算能力低的特点,提出了一种整句查找算法。文章首先介绍了使用倒序排列的文件结构,然后根据该文件结构设计出一种宽度为N的整句查找算法,并在手机S60平台上实现了整句输入系统。文章最后对该整句算法的输入正确率进行了测试。实验结果表明,该算法有着较好的效果。     

一种微机多点巡检仪前向通道电路

在分析了当前一些常见的微机多点温度巡检仪前向通道的基础上,提出一种“单恒流源供电、双多路开关同步切换式前向通道”新电路.该电路结构简单、体积小、制作成本低、信噪比大、工作可靠,已成功地用于生产实际。     

采用辅助转动装置的MIMO 系统双目标DPD 实验研究

文中介绍了一种双目标数字预失真(DPD)方案,并进行了实验研究。不增加系统复杂度的情况下, 可以有效地扩展MIMO 系统的线性化波束宽度。在发射机附近增设一个发射低功率信号的线性辅助转动装置,该 架构实现了MIMO 系统主波束线性化。实验平台由发射机系统和一个辅助转动装置组成,发射机天线阵列为1×4。 输入信号采用两个20 MHz 带宽峰均比分别为5. 7 dB 和5. 6 dB 的正交频分复用(OFDM)信号。实验研究结果表明, 采用了辅助转动装置的双目标DPD 方法后,邻信道功率比(ACPR)达到-50 dBc 以下的主波束线性化宽度可以扩展 到22°,同时信号归一化均方误差(NMSE)平均数值为-40 dB。该方案有效地拓宽了MIMO 系统线性化波束宽度。     

利用运动向量差值改善深度学习视频隐写分析

目的 针对现有深度学习视频隐写分析网络准确率不够高的问题,本文从视频压缩编码的原理出发,发掘嵌密编码参数与其他参数之间的关系,通过拓展检测空间,构造新的检测通道,改善现有深度学习视频隐写分析网络的检测性能。方法 以H. 265/HEVC(high efficiency video coding)压缩视频为例,首先通过分析运动向量的嵌密修改对运动向量差值的影响,指出可将运动向量差值作为新增的采样对象(或称检测对象);接着,提出一个构造运动向量差值检测矩阵的方法,解决了空域上采样样本稀疏、时域上样本空间位置无法对齐的问题;最后,将运动向量差值矩阵直接用于改善现有的VSRNet(video steganalysis residual network)、SCA-VSRNet(selection-channel-aware VSRNet)以及Q-VSRNet(quantitative VSRNet)等3个H. 265/HEVC深度学习视频隐写分析网络,分别得到IVSRNet(improved VSRNet)、SCA-IVSRNet(selection-channel-aware improved...     

Event-triggered-based integral reinforcement learning output feedback optimal control for partially unknown constrained-input nonlinear systems

In this paper, an adaptive output feedback event-triggered optimal control algorithm is proposed for partially unknown constrained-input continuous-time nonlinear systems. First, a neural network observer is constructed to estimate unmeasurable state. Next, an event-triggered condition is established, and only when the event-triggered condition is violated will the event be triggered and the state be sampled. Then, an event-triggered-based synchronous integral reinforcement learning (ET-SIRL) control algorithm with critic-actor neural networks (NNs) architecture is proposed to solve the event-triggered Hamilton–Jacobi–Bellman equation under the established event-triggered condition. The critic and actor NNs are used to approximate cost function and optimal event-triggered optimal control law, respectively. Meanwhile, the event-triggered-based closed-loop system state and all the neural network weight estimation errors are uniformly ultimately bounded proved by Lyapunov stability theory, and there is no Zeno behavior. Finally, two numerical examples are presented to show the effectiveness of the proposed ET-SIRL control algorithm.     

Adaptive fault-tolerant control for a class of flexible air-breathing hypersonic vehicles

In this paper, a novel adaptive fault-tolerant control (FTC) scheme is proposed for a class of flexible air-breathing hypersonic vehicles with unknown inertial and aerodynamic parameters and even input constraints. The fault model under consideration covers the case that all actuators suffer from unknown time-varying faults. In the controller design and stability analysis, we introduce new Lyapunov functions, some differentiable auxiliary functions, a bound estimation approach, and a Nussbaum function, which help us successfully circumvent the obstacle caused by the faults, input constraints, and flexible modes. In addition to higher reliability, the proposed scheme is able to ensure that all closed-loop signals are globally uniformly bounded and to steer the tracking errors of altitude and velocity into predefined arbitrarily small residual sets. As a result, the tracking accuracy can be designated in advance. Simulation results illustrate the effectiveness of the proposed scheme.     

面向递增累积型缺陷的灰盒模糊测试变异优化

大量访问越界、内存耗尽、性能故障等缺陷是输入中有效数据的规模过大,超过临界值引起的.而现有灰盒模糊测试技术中的数据依赖识别和变异优化技术大都针对固定规模输入数据格式,对规模递增输入数据的构造效率不高.为此,针对这类累积型缺陷模糊测试对应的状态特征值最优化问题,提出一种对特征值依赖的输入数据的格式判别和差分变异方法.根据引发特征值最值更新的有效变异的位置分布和发现频次特征,判别待发现缺陷状态优化是否依赖于输入中相关数据规模的增长,将引发最值更新的有效变异内容应用于规模递增输入数据生成,提升该类累积型缺陷的复现和定向测试效率.依据该思想,实现了模糊测试工具Jigsaw,在测评实验数据集上的实验结果表明提出的判别方法能够高效地区分特征值依赖的输入数据组织形式,且提出的差分变异方法显著提升了需要大量输入才能触发累积型缺陷的复现效率.     

Observer-based leader-following consensus of one-sided Lipschitz multi-agent systems over input saturation and directed graphs

This paper investigates a local observer-based leader-following consensus control of one-sided Lipschitz (OSL) multi-agent systems (MASs) under input saturation. The proposed consensus control scheme has been formulated by using the OSL property, input saturation, directed graphs, estimated states, and quadratic inner-boundedness condition by attaining the regional stability. It is assumed that the graph always includes a (directed) spanning tree with respect to the leader root to develop matrix inequalities for investigating parameters of the proposed observer and consensus protocols. Further, a new observer-based consensus tracking method for MASs with saturation, concerning independent topologies for communicating outputs and estimates over the network, is explored to deal with a more perplexing and realistic situation. In contrast to the traditional methods, the proposed consensus approach considers output feedback and deals with the input saturation for a generalized class of nonlinear systems. The efficiency of the obtained results is illustrated via application to a group of five moving agents in the Cartesian coordinates.     

Preview control of polytopic time-varying systems subject to actuator saturation

In this study, a novel method is proposed to track a previewable reference signal in the polytopic time-varying system with input saturation. Firstly, an augmented model containing future information is constructed using a new formal variable. This leads to the tracking control problem of polytopic time-varying system with input saturation is transformed into a stability problem of augmented error system. Next, the state and static output feedback preview controls are introduced, and the corresponding controller gains are produced by the proposed conditions. Two examples are presented to validate the effectiveness of the proposed preview controller.