Automatic modulation classification based on AlexNet with data augmentation

Deep learning (DL) requires massive volume of data to train the network. Insufficient training data will cause serious overfitting problem and degrade the classification accuracy. In order to solve this problem, a method for automatic modulation classification ( AMC) using AlexNet with data augmentation was proposed. Three data augmentation methods is considered, i. e. , random erasing, CutMix, and rotation. Firstly, modulated signals are converted into constellation representations. And all constellation representations are divided into training dataset and test dataset. Then, training dataset are augmented by three methods. Secondly, the optimal value of execution probability for random erasing and CutMix are determined. Simulation results show that both of them perform optimally when execution probability is 0.5. Thirdly, the performance of three data augmentation methods are evaluated. Simulation results demonstrate that all augmentation methods can improve the classification accuracy. Rotation improves the classification accuracy by 13.04% when signal noise ratio (SNR) is 2 dB. Among three methods, rotation outperforms random erasing and CutMix when SNR is greater than - 6 dB. Finally, compared with other classification algorithms, random erasing, CutMix, and rotation used in this paper achieved the performance significantly improved. It is worth mentioning that the classification accuracy can reach 90.5% with SNR at 10 dB.     

基于直觉模糊熵的混合粒子群优化算法

为了提升粒子群算法的全局寻优与局部精细搜索能力并加快收敛速度,提出了基于直觉模糊熵的混合粒子群优化算法.该算法采用粒子的历史最优解信息构造直觉模糊熵的自适应函数,并将熵值作为扰动因子动态调节惯性权重,同时建立自适应全局最优粒子学习策略对扰动后的粒子进行训练,在保持多样性传播的基础上选择学习对象,使粒子探索更多新区域,实现种群间的协作与并行进化.通过仿真实验,将本文算法与两种衍生算法以及其他改进粒子群算法在11个测试函数上进行比较,结果表明,本算法在求解精度、收敛速度和寻优效率上均有更好表现.     

混凝土建筑的艺术魅力

混凝土作为建筑材料被广泛应用于建筑工程中,由于其具有可塑性及适应能力强等特点,学界普遍聚焦于混凝土的改性工作,忽略了其自身艺术价值。以混凝土艺术特征为研究对象,结合典型案例,从结构、材质和文脉3方面展现混凝土建筑的独特魅力,以期为混凝土材料在当代建筑设计中的应用提供参考。     

谈格宾石笼在新疆伊犁河口防护工程中的应用

结合新疆伊犁河口防护工程实例,对格宾笼防护工程的结构特点作了介绍,主要研究了格宾石笼护坡的设计参数,并从基础处理、土工布铺设、格宾笼组装等方面阐述了具体的施工要求,以充分发挥该技术的优势。     

楔形角对楔形桩负摩阻力承载特性的有限元分析

由于楔形桩存在楔形角，在桩周土体沉降时，使桩土之间有相互脱离的趋势，进而减小界面应力，最终能有效控制桩侧负摩阻力的大小。基于数值分析，研究了楔形角对负摩阻力的影响。结果表明，无论在何种荷载等级下，桩身轴力随深度的增加，均呈现出先增大后减小的趋势，在中性点位置取得极大值；随着楔形角的增大，楔形桩对负摩阻力的削减作用愈发明显；分别利用轴力最大点、摩阻力零值、相对位移零值得出的中性点位置基本相同，并且随着楔形角α从0°增大到3.00°，中性点深度逐渐减小。