In this paper, the continuous time recurrent neural network is proposed to solve the functional minimization problem, which is often involved in estimation and control.
针对信息科学和控制理论中经常涉及的一类泛函极值问题，提出基于连续回归神经网络的求解方法。
The problem of robust state estimation for continuous-time singular linear systems with un-certain noise is considered. A kind of practical algorithm of optimum recurrence estimation is obtained.
本文讨论了一类具有不确定噪声的连续广义线性系统的鲁棒状态估计问题，文章提供了一种比较实用的状态估计方法。
A data aided symbol timing estimation algorithm was proposed for burst-mode space-time trellis coded multi-level continuous phase modulation (STTC-MCPM) systems in Rayleigh fading channels.
针对瑞利衰落信道中突发模式的空时网格编码的多电平连续相位调制(STTC - MCPM)系统，提出了一种基于数据辅助的符号定时估计算法。
A data aided symbol timing estimation algorithm was proposed for burst-mode space-time trellis coded multi-level continuous phase modulation (STTC-MCPM) systems in Rayleigh fading channels.
针对瑞利衰落信道中突发模式的空时网格编码的多电平连续相位调制(STTC - MCPM)系统，提出了一种基于数据辅助的符号定时估计算法。
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