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ESN (Echo state network) is a new type of RNN (recurrent neural network) based on the "reservoir". 该方法基于一种具备“储备池”机制的新型递归神经网络：回声状态网络(ESN)。
The network was compared with recurrent neural network (RNN) by predicting exhaust gas temperature (EGT). 分别利用递归神经网络和双隐层过程神经网络对发动机排气温度裕度进行仿真预测。
By using the dynamic mapping ability of recurrent neural network (RNN), the identifier of ASVG is constructed. 利用递归神经网络的动态映射能力，实现了静止无功发生器的递归神经网络建模，构造了ASVG递归神经网络模型。
Program for training and testing the Elman Recurrent Neural Network model when used to predict has been tested. (译)：计划的培训和测试的Elman递归神经网络模型用于预测时，已经过测试。
The dynamic recurrent neural network is analyzed, andhow to use it for system identification is also analyzed. 对所提出的动态递归神经网络进行了分析,以及如何利用它们来进行系统辨识。
A novel fast convergence blind equalization algorithm based on recurrent neural network is proposed. 提出了一种新的基于递归神经网络的快速收敛盲均衡算法。
As a new type of recurrent neural network,echo state network(ESN) is applied to nonlinear system identification and chaotic time series prediction. ESN(回声状态网络)是一种新型的递归神经网络;可有效处理非线性系统辨识以及混沌时间序列预测问题.
RPE (recursive prediction error) algorithm with the advantage of fast convergence is applied to training the recurrent neural network. 采用递推预报误差算法训练神经网络，具有收敛速度快、收敛精度高的特点。
For the white-box optimization，the merits and demerits of EA and Recurrent Neural Network（RNN），and the survey on popular EAs and their common improvements are discussed. 对于白箱优化问题，阐述了进化算法与反馈神经网络的优缺点和目前流行的进化算法及其通用改进策略。
Because there are no parameters that characterize air inflow in each cycle, dynamic recurrent neural network (Elman) was adopted for forecasting engine's air inflow in each cycle. HCCI汽油机没有能直接表征发动机每循环进气量的参数，因此，采用动态递归神经网络（Elman网络）预测HCCI发动机每循环的进气量。
The optimal reactor temperature profiles were obtained via the PSO-SQP algorithm solving maximum product concentration problem based on recurrent neural network（RNN）. 基于主产物浓度和反应温度的递归神经网络（RNN）模型，使用混合PSO-SQP算法求解该间歇反应主产物产率最大化问题，进而得到反应温度优化曲线。
The hybrid Control of a permanent magnet linear synchronous motor (PMLSM) servo-drive system using an adaptive recurrent neural network was put forward to solve the problem of poor stable precision in the servo system of packaging binding machine. 摘要根据裹包机的驱动系统控制精度较差的问题，提出采用递归神经网络自适应混合控制线性同步电动器驱动机系统。
An algorithm is proposed to solve the Nash equilibrium solution for an n-person noncooperative dynamic game by an annealing recurrent neural network for extremum seeking algorithm(ESA). 针对如何解算n人非合作的动态博弈对策中的纳什均衡解问题,提出一种利用退火回归神经网络极值搜索算法解算纳什均衡解的方法。
Robust periodic motion control of the mover of a permanent magnet (PM) linear synchronous motor (LSM) drive is achieved by use of a recurrent neural network (RNN) controller in this study. 摘要本研究利用递迴式类神经网路控制器来达成永磁线型同步马达动子位置之周期性运动的强健性控制。
RNN theoretical basis with the introduction of some Recurrent Neural Networks models. 介绍一些递归神经网络模型。
A new blind equalization algorithm based on diagonal recurrent neural networks (DRNN) is proposed. 提出了一种基于对角递归神经网络的盲均衡算法。
Because there are feedback units in the structure of Elman recurrent neural network(Elman RNN), has dynamic characteristics, it is more suitable for simulate non-linear dynamic system. 软测量建模选用Elman型回归神经网络，因为它在结构中加入了反馈单元，从而具有动态特性，适合于非线性动态系统建模。
An algorithm is proposed to solve the Nash equilibrium solution for an n-person noncooperative dynamic game by an annealing recurrent neural network for extremum seeking algorithm (ESA). 摘要针对如何解算n人非合作的动态博弈对策中的纳什均衡解问题，提出一种利用退火回归神经网络极值搜索算法解算纳什均衡解的方法。
This paper presents an adaptive congestion control model in ATM networks at the user to network interface by using a diagonal recurrent neural network (DRNN) as an predictor. 提出一种在用户-网络接口处利用对角递归神经网络(DRNN)作为自适应预测器，实现ATM网络自适应拥塞控制的模型。
ANN is usually divided into two kinds: one is the feed-forward neural networks (i.e. no feedback neural networks), the other is recurrent neural networks (RNN) (i.e. feedback neural networks). 人工神经网络通常分为两类；一类是前馈神经网络（即没有反馈的神经网络）；另一类是递归神经网络（即有反馈的神经网络）。