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The calculation results show that the normalized polynomial-match for non-linear function and neural network can match experimental data more accurate than other arithmetic methods for compensating the offset thermal drift of pressure sensor.

结果表明,非线性函数多项式拟合规范化方法和神经网络法拟合出的数据精度很高,取得了其他方法无法达到的补偿效果。

The normalized vector is used as the input of RBF NN, and target recognition is performed based on this, which leads to a satisfactory recognition result.

并对该特征向量进行对数归一化,将归一化的特征向量作为径向基函数神经网络的输入,在此基础上进行识别,达到较好的识别效果。

At first, draws the atomic seeps into executing probabilistic matrix and transferring probabilistic matrix. Change LEG for probability logic seeps through picture of probabilistic logical exploitation graph PLEG, then explains the PLEG problem to the solution of MDP value function and optimal policy.

本文提出了一种基于MDP的风险概率计算模型PLEG-MDP,首先通过引入原子渗透执行概率矩阵和转移概率矩阵,将LEG转换为概率逻辑渗透图PLEG,然后将PLEG解释为MDP,进而求解MDP问题的价值函数和最优策略,其分别对应着目标网络的最大风险概率和风险路径。

In order to overcome the shortagings of current algorithms, a new learning algorithm called as"Recurrent Generalized Inverse Peneaty" algorithm is derived via the optimality principle.

主要结果有:(1)根据最优化原理提出了新的训练GSLN网络的学习算法,"递推广义逆罚函数"算法,以便克服现有算法的缺陷;(2)。

The calculation methods of basis function of high order CMAC-NN are given and the simulation is carried out.

研究了CMAC网络的结构及基本原理,提出了中间层作用基函数地址的计算方法。

In consideration of the complexity of the aggregation operation of time in process neural networks, a new learning algorithm based on function orthogonal basis expansion is proposed.

该文在考虑过程神经网络对时间聚合运算的复杂性的基础上,提出了一种基于函数正交基展开的学习算法。

Based on polynomial curve-fitting theory, a Laguerre orthogonal basis feed-forward neural network is constructed.

根据多项式理论,构造了一种以Laguerre正交多项式作为隐层神经元激励函数的前向神经网络模型。

Keywords: process neural network;orthogonal function basis;aggregation operation;learning algorithm;complexity of computation

该文在考虑过程神经网络对时间聚合运算的复杂性的基础上,提出了一种基于函数正交基展开的学习算法。

The results show that the fitting curve is very smooth using neural network algorithm with Fourier orthogonal basis function, and its fitting precision is very high.

研究结果表明,用傅立叶正交基函数神经网络算法拟合的曲线十分光滑,拟合精度高。

Differential Evolution Orthogonal Least Square algorithm for RBF network is presented,a hybrid algorithm blending Orthogonal Least Squares method with Differential Evolution algorithm.

研究用于径向基函数网络训练的一种微分进化正交最小二乘算法。

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