信息时代马克思主义哲学育人价值的实现

信息时代对学生的文化判断和道德判断能力提出了挑战 ,也对马克思主义哲学教育提出了更高的要求。通过分析马克思主义哲学育人价值及其体现 ,指出在现代课堂教学中 ,理论的选择和比较是马克思主义哲学育人价值实现的重要环节。     

一类非线性二阶多点边值问题多个正解的存在性研究

通过定义适当的锥,运用锥映射的不动点定理,结合上下解方法,给出了二阶多点边值问题多个正解存在性的判定方法.作为特例,获得了三点边值问题多个正解存在性的判定依据,从而推广了相关文献中关于二阶三点边值问题正解存在性的结果.     

超音速微粒轰击表面纳米化设备研制

超音速微粒轰击是材料表面纳米化的重要手段,性能优异的专用设备是实现这一工艺的前提。为此,采用数值模拟分析的方法研制了超音速微粒轰击喷枪,在距喷枪出口50mm处获得了平均约320m/s的轰击粒子速度;在对机器人选型和控制系统设计的基础上,集成了超音速微粒轰击表面纳米化设备;应用该设备实现了对38CrSi中碳钢的表面纳米化处理,验证了研制设备的性能。     

A novel noise reduction technique for underwater acoustic signals based on complete ensemble empirical mode decomposition with adaptive noise,minimum mean square variance criterion and least mean square adaptive filter

Underwater acoustic signal processing is one of the research hotspots in underwater acoustics. Noise reduction of underwater acoustic signals is the key to underwater acoustic signal processing. Owing to the complexity of marine environment and the particularity of underwater acoustic channel, noise reduction of underwater acoustic signals has always been a difficult challenge in the field of underwater acoustic signal processing. In order to solve the dilemma, we proposed a novel noise reduction technique for underwater acoustic signals based on complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN), minimum mean square variance criterion (MMSVC) and least mean square adaptive filter (LMSAF). This noise reduction technique, named CEEMDAN-MMSVC-LMSAF, has three main advantages: (i) as an improved algorithm of empirical mode decomposition (EMD) and ensemble EMD (EEMD), CEEMDAN can better suppress mode mixing, and can avoid selecting the number of decomposition in variational mode decomposition (VMD); (ii) MMSVC can identify noisy intrinsic mode function (IMF), and can avoid selecting thresholds of different permutation entropies; (iii) for noise reduction of noisy IMFs, LMSAF overcomes the selection of decomposition number and basis function for wavelet noise reduction. Firstly, CEEMDAN decomposes the original signal into IMFs, which can be divided into noisy IMFs and real IMFs. Then, MMSVC and LMSAF are used to detect identify noisy IMFs and remove noise components from noisy IMFs. Finally, both denoised noisy IMFs and real IMFs are reconstructed and the final denoised signal is obtained. Compared with other noise reduction techniques, the validity of CEEMDAN-MMSVC-LMSAF can be proved by the analysis of simulation signals and real underwater acoustic signals, which has the better noise reduction effect and has practical application value. CEEMDAN-MMSVC-LMSAF also provides a reliable basis for the detection, feature extraction, classification and recognition of underwater acoustic signals.     

基于水下声场信息的三维航路规划研究

针对目前大规模水下复杂战场环境中的航路规划困难的问题。设计了一种以距离值传递法为基础的航路规划方法,该方法以水下声场为主要威胁源,运用三维抛物方程(PE)模型计算水下声场数据,并以此建立三维水下战场环境。利用限制线性八叉树的方法对数据场进行数据分割,从而达到对搜索空间的压缩,最后通过距离值传递法搜索得到最佳航路。仿真结果表明该方法较快的实现了三维声场环境下的不同起始点、多目标寻径,满足一定条件下航路规划要求。     

GM（1，1）组合优化模型

从影响GM（1，1）模型产生误差的两个主要原因出发，重新选择灰导数，并基于Newton．Cote’s积分公式和相邻最近插值方法构造出GM（1，1）组合模型，提出了求该组合模型参数的计算方法，通过实例验证了组合模型的模拟精度，具有重要的应用价值。