Will you design a new neural network learning algorithm, or add a cool sound effect?
请问你会设计一个新的神经网络学习算法，或添加更酷的声音效果吗？
The easy-to-use interface allows you to set minimal conditions for preprocessing and neural network learning.
易于使用的界面，使您能够设置最小的条件进行预处理和神经网络学习。
Radial Basis Function (RBF) neural network learning algorithm based on immune recognition principle is proposed.
提出了一种基于免疫识别原理的径向基函数神经网络学习算法。
Neural network learning easy language source code routine program demonstrates a single sensory neural training.
神经网络学习易语言源码例程程序演示了单层感知神经训练。
A Radial Basis Function (RBF) neural network learning algorithm based on immune recognition principle is studied.
提出了一种基于免疫识别原理的径向基函数神经网络学习算法。
A Radial Basis Function (RBF) neural network learning algorithm based on immune recognition principle is proposed.
提出了一种基于免疫识别原理的径向基函数神经网络学习算法。
Specifies the percentage of training cases used to calculate the holdout error, which is used as part of the stopping criteria during neural network learning.
指定用于计算？效组错误的培训案例之百分比，以在类神经网路学习期间作为停止准则的一部分。
In this paper, we proposed a parallel BP neural network learning algorithm with the support of PC cluster under the circumstance of PVM (parallel Virtual Machine).
本文提出了一种利用微机机群来实现并行处理，在并行编程环境P VM中实现BP神经网络的并行学习算法。
BP algorithm is the most popular training algorithm for feed forward neural network learning. But falling into local minimum and slow convergence are its drawbacks.
BP算法是前馈神经网络训练中应用最多的算法，但其具有收敛慢和陷入局部极值的严重缺点。
In order to prevent neural network learning from getting into local extreme point, artificial immune network algorithm was used to optimize neural network's parameters.
为了避免神经网络的学习过程陷入局部极值点，采用人工免疫网络优化神经网络的参数。
Some recent neural network research also indicates that deep sleep may be important in helping clear the brain for new learning the next day.
最近的一些关于神经网络的研究发现：深睡眠对保持头脑清醒以进行第二天的学习非常重要。
For instance, a certain kind of basic neural network, the perceptron, is biased to learning only linear functions (functions with inputs that can be separated into classifications by drawing a line).
例如，某些基本的神经网络，它们的感知器只倾向于学习线形函数(通过划一条线可以把函数输入解析到分类系统中)。
With the study of neural network model, this paper advances some of improvement and optimization techniques that can accelerate the learning speed of network and increase the stability of model.
本文从神经网络模型的结构出发，对学习算法提出了一系列改进和优化措施，以加快网络的学习速度，并增加模型的稳定性。
As the basic unit of Neural Network, Neural Controllers with different learning rules will result in different control effects for the learning process of synaptic weights.
作为神经网络控制的基本单元，采用不同学习规则的神经元控制器，对神经元的学习过程将产生不同的影响。
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。
The topologic structure and learning algorithm of the rough neural network are given, and the approximation theorem of the rough neural network is presented.
给出了粗糙神经网络的拓朴结构和学习算法以及粗糙神经网络的逼近定理。
The simulation results prove that the neural network controller has self-learning and self-adaptive ability by comparison with PD controller. The position tracking control obtains satisfactory effect.
结果表明，相对于常规PD控制器，该神经网络控制器具有自学习、自适应功能，位置跟踪获得了满意的控制效果。
Based on the learning characteristic of neural network and the function approximation ability of the wavelet, a new self tuning control algorithm is presented.
依据小波的非线性逼近能力和神经网络的自学习特性，提出了一种基于小波神经网络模型的自校正控制算法。
In this paper, we present a method of training a feedforward neural network using supervised learning scheme to balance an inverted pendulum and cart system.
本文将专家在平衡—模拟倒摆小车时记录下来的数据经处理后，用监督式学习的方法训练一前置式神经网络。
Presents a method of training a feedforward neural network using supervised learning scheme to balance an inverted pendulum and cart system.
采用平衡的倒摆小车所记录下来的数据，经处理后用有师学习方法来训练前馈神经网络。
Based on fuzzy neural network, this paper presents a self learning controller used to industrial kiln temperature system.
本文提出一种模糊神经网络自学习控制方法，并应用于窑炉温度控制系统中。
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。
The learning process of a neural network is considered the process in which neural network variables are changed with a time series of input signals generated from a stochastic information source.
根据该理论，学习过程就是由随机信息源产生的输入信号驱动神经网络参数不断修改的过程；
A fuzzy neural network prediction control model is stated by using the logic inference performance of fuzzy control and the learning ability of neural network.
应用模糊控制的逻辑推理性能，借助神经网络的学习能力，提出了一种模糊神经网络预测控制模型。
Neural network is good at learning, but the result is not easy to understand.
神经网络擅长于学习，但是结果不容易被人理解。
PN model, LAC neural network and its learning algorithm are all put forward first time in this thesis.
PN神经元模型、lac神经网络及学习算法，都是本文首次提出的。
PN model, LAC neural network and its learning algorithm are all put forward first time in this thesis.
PN神经元模型、lac神经网络及学习算法，都是本文首次提出的。
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