ID 原文 译文
48476 在复杂电磁环境中,如何对电子设备产生的电磁辐射进行准确测量一直是亟待解决的典型工程问题。 In a complex electromagnetic environment, how to accurately the electronic equipment produced by electromagnetic radiation measurement has always been a typical engineering problem to be solved.
48477 提出了一种具有环境干扰抑制效果的外场辐射发射测试新方法,不同于传统的基于自适应噪声抵消方式的虚拟暗室测试方法,其采用空间谱估计和自适应宽带波束形成等阵列信号处理方式以实现对环境干扰的空域滤除。 Put forward a kind of environmental interference suppression effect, a new method of field radiation emission test, different from the traditional adaptive noise cancellation method based virtual darkroom test method, its using spatial spectrum estimation and adaptive broadband beamforming array signal processing method to realize the interference to the environment such as spatial filtering.
48478 计算机仿真以及试验结果证明,所提方法在保证受试设备辐射特性无失真的情况下,能同时有效滤除被测信号中混迭的同频、宽带等不同体制的环境干扰,弥补了虚拟暗室测试技术的不足,提高了外场电磁辐射测量的速度和精度。 Computer simulation and experimental results show that the proposed method in the guarantee equipment radiation characteristic subjects without distortion, can effectively filter out with mixed up in the measured signal frequency, different system environment, such as broadband interference, make up for the deficiency of the virtual darkroom test technology, improve the field electromagnetic radiation measurement speed and precision.
48479 针对蚁群算法收敛速度慢,容易陷入局部极值的缺点,提出将量子进化算法与蚁群算法相融合的新算法。 In view of the ant colony algorithm is slow convergence speed, easy to fall into local extremum, quantum evolutionary algorithm and ant colony algorithm combines the new algorithm.
48480 在该算法中,蚂蚁当前位置用量子比特的两个概率幅表示,与普通蚁群算法相比,个体数量相等时,新算法的搜索空间将加倍,同时用量子非门来实现变异操作,相比传统算法,在寻优过程中具有更好的种群多样性并有效克服了蚁群算法的早熟及停滞现象。 In this algorithm, the ant in the current position, said two of quantum bit probability amplitude compared with ordinary ant colony algorithm, equals the number of individuals, the searching space of the new algorithm will double, and at the same time with quantum gate to realize mutation, compared with the traditional algorithm, the optimization process has better diversity of population and effectively overcome the premature of ant colony algorithm and stagnation phenomenon.
48481 将此算法用于图像分割,实验结果表明,该方法有效解决了蚁群算法收敛速度慢和容易陷入局部极值的问题,而且在分割速度和精度上得到了较大提高。 Use this algorithm for image segmentation, the experimental results show that this method is effective to solve the slow convergence speed and ant colony algorithm easy to fall into local extremum problems, and on the segmentation speed and precision has been improved greatly.
48482 针对现有基于误差反向传播算法的多层感知器神经网络分类器在信号识别中存在收敛速度缓慢、出现假饱和现象等问题,采用蜂群算法提取信号的联合特征模块,提出快速支持、超级自适应误差反向传播、共轭梯度3种不同算法分别应用于多层感知器神经网络分类器,实现对通信信号的自动识别。 In view of the existing based on error back propagation algorithm of multilayer perceptron neural network classifier in signal recognition problem such as slow convergence speed, appear false saturation phenomenon, the joint characteristics of the colony algorithm to extract the signal module, support, super fast adaptive error back propagation, conjugate gradient three different algorithms are applied to multi-layer perceptron neural network classifier, realize the automatic recognition of communication signals.
48483 所提算法和误差反向传播算法相比有更高的识别率。 The proposed algorithm and error back propagation algorithm has a higher recognition rate.
48484 仿真结果表明,所提算法能够克服误差反向传播算法的缺陷,在隐藏层神经元仅为20个、信噪比为4dB条件下,3种算法的识别率均高于95%,且系统易于实现,在信号识别中具有广泛的应用前景。 The simulation results show that the proposed algorithm can overcome the defects of error back propagation algorithm, neurons in hidden layer was only about 20, the signal-to-noise ratio is 4 db conditions, three kinds of algorithm of recognition rate above 95%, and the system is easy to implement, in signal recognition has wide application prospect.
48485 在多传感器数据融合系统中,航迹关联是后续融合处理的基础。 In the multi-sensor data fusion system, the correlation is the foundation of subsequent fusion processing.