In this paper, a novel fast learning algorithm for multilayered feedforward neural network is introduced.
本文提出一种前馈神经网络的快速学习算法。
The compensation fuzzy neural network (CFNN) with fast learning algorithm and compensation fuzzy inference is introduced in this paper.
本文介绍了一种具有快速学习算法、能够执行补偿模糊推理的补偿模糊神经网络。
This paper applies parallel tangents of nonlinear programming during the weights training of neural network and puts forward a neural network in view of fast learning algorithm.
因此，作者将非线性规划的平行切线算法用于神经网络的权值学习，提出了一种具有快速学习算法的神经网络。
Aiming at the issue about multi-step prediction of the traffic flow chaotic time series, a fast learning algorithm of wavelet neural network (WNN) based on chaotic mechanism is proposed.
针对交通流量混沌时间序列多步预测的问题，提出了一种基于混沌机理的小波神经网络(WNN)快速学习算法。
The simulation and motor control show that the new algorithm has fast learning rate, good convergence properties and can overcome the defects of traditional PID algorithm.
仿真实验及在伺服电机转速控制中的应用表明，该算法具有较快的学习速度及良好的收敛性能，并有效地克服了传统PID算法的缺陷。
A new geometric fast incremental learning algorithm for support vector machines (SVM) was proposed.
提出了一种新的基于壳向量的增量式支持向量机快速学习算法。
Experiment shows neural network classifier that is optimized by algorithm could not only have fast learning speed but also ensure accuracy of classification.
实验结果表明：算法优化后的神经网络分类器不但学习速度快，还能保证分类精度。
The new algorithm, compared to the BP algorithm, has the fast learning rate and good convergence properties.
该算法有效地改进了神经元网络的学习收敛速度，取得了比常规BP算法更好的收敛性能和学习速度。
The simulation result is that the Fuzzy forward neural networks which is trained by this algorithm have good non-logic generalization and feature extraction ability, as well as fast learning speed.
模拟结果表明利用该算法训练的模糊层次神经网络具有较好的非逻辑归纳能力和特征抽取能力，并且学习速度也大大加快。
Simulation shows that the learning algorithm has a fast convergence speed and good stability.
仿真表明，该学习算法收敛速度快、稳定性好。
This algorithm is fast, incremental learning, and it takes less support vectors!
本算法具有速度快、增量学习、使用的支持向量少等显著优点。
To accelerate the training speed of BP network, a joint-optimized fast BP learning algorithm is proposed.
针对BP网络学习速度的缓慢性，本文提出了一种联合优化后的快速学习算法。
A fast incremental learning algorithm is proposed.
提出了一种快速、增量式的学习算法。
The algorithm is applied to XOR problem and nonlinear function approximation. Simulation results show that the chaos-BP algorithm needs shorter learning time than that of the standard BP and fast BP.
采用混合算法对XOR问题和非线性函数进行仿真，结果表明该算法明显优于标准BP算法和快速BP算法。
In this paper, a kind of variable metric fast second order nonlinear optimization algorithm is proposed, where a second order interpolating method is used in the optimization of learning rate.
神经网络的辨识采用变尺度二阶快速学习算法，利用二阶插值法来优化搜索学习速率。
In this paper, a kind of variable metric fast second order nonlinear optimization algorithm is proposed, where a second order interpolating method is used in the optimization of learning rate.
神经网络的辨识采用变尺度二阶快速学习算法，利用二阶插值法来优化搜索学习速率。
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