摘要
在非相参积累检测系统中 ,容易得到雷达虚警概率关于阈值的解析表达式 ,但难以得到阈值关于虚警概率的解析表达式 ,利用径向基函数 (RBF)神经网络具有良好的逼近任意非线性映射和快速收敛的特点 ,提出了一种精确估计阈值的RBF神经网络方法。仿真结果表明 。
It is easy to yield the analytical expression of the probability of false alarm with respect to the threshold, but hard to obtain the analytical expression of the threshold with respect to the probability of false alarm. By making use of the perfect properties of radial basis function (RBF) neural networks, such as approaching arbitrary non-linear mapping and quick convergence, a new scheme based modified RBF neural networks is proposed in obtaining threshold estimation. Simulation results show that the proposed scheme is of higher accuracy in threshold estimation.
出处
《空军工程大学学报（自然科学版）》
CSCD
2004年第3期24-27,共4页
Journal of Air Force Engineering University(Natural Science Edition)
基金
国家"8 6 3"高技术研究发展计划资助项目 (2 0 0 2AA135 32 0 )
关键词
径向基函数
神经网络
阈值
检测概率
RBF
neural networks
threshold
probability of detection
