In this paper, the continuoustime 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。
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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.
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.