基于递推技术的算法设计方法的应用研究

算法是计算机科学的核心,算法设计对于开发正确、高效的程序至关重要。基于递推技术的算法设计方法通过形式化推导保证算法的可靠性,同时能较好地提高算法程序的效率。本文通过两个实例,详细介绍基于递推技术的算法设计方法形式化推导算法程序的过程。     

一种基于光照变化补偿的颜色识别方法

针对RoboCup中型组足球机器人比赛中光照变化会使颜色发生色彩漂移,影响颜色识别的准确性问题,提出一种基于光照变化补偿的颜色识别方法。该方法首先利用球的历史信息预测球的位置,然后在较小的区域内用基于色调直方图反向投影的方法找到球后,通过球的亮度直方图的变化计算出光照变化率,用于动态补偿颜色查找表。实验表明该方法能提高颜色识别的光照自适应性。     

Response of Hydrodynamics and Water-quality Conditions to Climate Change in a Shallow Lake

Lake water resources operation and water quality management come up with higher challenges due to climate change. The frequency and intensity of extreme hydrological events are increasing under global warming, which may directly lead to more uncertainty and complexity for hydrodynamic and water-quality conditions in large shallow lake. However, studies about effects of climate change on lake hydrodynamic and water-quality conditions are not enough. Thus, a coupled model is es-tablished to investigate the potential responses of lake water level, flow field and pollutant migra-tion to the changing climatic factors. The results imply that water flow capacity and self-purification in the Hongze Lake can be improved by west, northwest, north, south and southeast winds indi-cating wind filed change has a great effect on the hydrodynamic and water-quality conditions in large shallow lake. It is further observed that both hydrodynamics and water quality are more sensitive to rainfall change than to temperature change; compared to the effect from temperature and rainfall, the effect from wind field appear to be more pronounced. Moreover, the results verify the feasibility of coupling basin hydrological model with lake hydrodynamic and water quality model. To the best of knowledge, the coupled model should not be used until independent calibra-tions and verifications for hydrodynamics and water quality modeling, the hydrological model and the coupled model.

     

Protect privacy of deep classification networks by exploiting their generative power

Machine Learning - Research showed that deep learning models are vulnerable to membership inference attacks, which aim to determine if an example is in the training set of the model. We propose a...     

Identifying epidemic spreading dynamics of COVID-19 by pseudocoevolutionary simulated annealing optimizers

Neural Computing and Applications - At the end of 2019, a new coronavirus (COVID-19) epidemic has triggered global public health concern. Here, a model integrating the daily intercity migration...     

A deep multi-source adaptation transfer network for cross-subject electroencephalogram emotion recognition

Neural Computing and Applications - In real-world application of affective brain–computer interface (aBCI), individual differences across subjects and non-stationary characteristics of...     

A steel surface defect inspection approach towards smart industrial monitoring

Journal of Intelligent Manufacturing - With the advance in Industry 4.0, smart industrial monitoring has been proposed to timely discover faults and defects in industrial processes. Steel is widely...     

高灰度级TFT-LCD显示系统的实现

提出了一种以FPGA为核心控制器的高灰度级TFT-LCD显示系统的设计方案。该系统采用幅值-帧速率控制调制-空间混合灰度调制方法,首先将10 bit的R、G、B信号分割成高8 bit数据和低2 bit数据,低2 bit数据经过空间处理后平均分到4个相邻的8 bit数据上,然后把这8 bit数据继续分割成高6 bit数据和低2 bit数据,其中高6 bit数据用于幅值调制,低2 bit数据用于帧速率控制调制,从而实现1 024个灰度等级显示。试验结果表明,该系统具有良好的显示效果和较高的显示灰度等级。     

基于D-FNN的混沌铁磁谐振系统非线性补偿控制方法

针对电网混沌铁磁谐振系统产生的混沌现象,提出基于动态模糊神经网络的混沌铁磁谐振系统非线性补偿控制方法。该方法采用动态模糊神经网络来逼近系统的非线性部分,消除了过电压的混沌现象,将系统稳定到目标位置,实现了对系统的非线性补偿控制。Matlab仿真结果表明,基于动态模糊神经网络的非线性补偿控制方法控制结果正确,响应快速。     

飞机振动特性激光测量与分析

飞机振动特性测量与分析,对于飞机识别和探测系统的设计与评估是至关重要的;在简要介绍了振动特性测量理论之后,针对外场环境条件,设计了飞机振动特性激光测量装置和测量方法,并经过实验室验证;在全尺寸飞机试验与测量过程中,获得了有效的原始测量数据,计算出飞机振动特征量:平均中心频率和二阶中心矩;同时指出了在飞机振动测量中应注意的问题;试验表明,飞机振动特性测量与分析方法正确、有效。