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1)  perceptron training algorithm
感知机学习算法
1.
This paper pointed out some factors comprehended through computer emulation which affect the resolution of MUSIC method, analysed the reasons which make the resolution of MUSIC method lower, and expounded a method for improving the resolution of MUSIC method with the perceptron training algorithm.
文中指出了通过计算机仿真了解到的影响MUSIC测向算法分辨率的一些因素 ,分析了造成MU SIC测向算法计算机仿真的分辨率较低的原因 ,并提出了一种用人工神经网络中的感知机学习算法改善MU SIC测向算法计算机仿真分辨率的方
2)  perception learning rule
感知机学习规则
1.
In this paper,according to the network characteristic and the shortcoming of the existing algorithm,by analyzing the Madaline network work principle and its learning algorithm MRII,propose an improvement algorithm that combines the MRII algorithm and the perception learning rule that will improve the performance of the network learning.
根据Madaline网络工作原理,针对其网络特点和现有算法中存在的缺点,提出将MRⅡ算法与感知机学习规则相结合的改进的学习算法,使每个样本学习后权值的改动尽量小,从而减少它对其它样本学习产生的影响,达到提高网络学习能力的目的。
3)  Perceptual learning
感知学习
1.
METHODS: The perceptual learning model was programmed and applied in 29 college students, who were randomly divided into 4 groups (6 students in group 1 and 2 respectively, 7 in group 3 and 10 in group 4).
目的:建立合成语音的感知学习模型并验证该模型的学习效应。
2.
Through perceptual learning training,adult patients with amblyopia can improve visual ability on contrast sensitivity and visual acuity.
通过视知觉感知学习训练,可以在一定程度上提高成人弱视患者的对比敏感度和视觉敏锐度,从而改善视觉缺损状况。
3.
Research models of perceptual learning are very helpful to reveal the intrinsic mechanisms of learning and memory.
针对感知学习的研究模型有助于揭示人类学习和记忆活动的内在机制。
4)  perception algorithm
感知算法
5)  machine learning algorithm
机器学习算法
1.
For the application of new machine learning algorithms to dam safety monitoring system,this paper presents an integration method based on component object model(COM) technique.
为方便在大坝安全监控系统中灵活应用新型机器学习算法,提出了一种应用组件对象模型(COM)技术将机器学习算法集成到大坝安全监控系统中的方法,相比于在开发系统中直接对机器学习算法进行编程,该方法可节省大量的编程时间,缩短开发周期,效果较好。
2.
For this purpose, machine learning algorithms based on semantic web have been done further researches into in this paper.
为了实现机器的智能化,本文对基于语义Web的机器学习算法作了深入研究。
6)  Bayes machine learning algorithm
Bayes机器学习算法
补充资料:逆推学习算法
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性质:又称逆推学习算法,简称BP算法,是1986年鲁梅哈特(D. E. Rumelhart)和麦克莱朗德(J. L. McClelland)提出来的。用样本数据训练人工神经网络(一种模仿人脑的信息处理系统),它自动地将实际输出值和期望值进行比较,得到误差信号,再根据误差信号从后(输出层)向前(输入层)逐层反传,调节各神经层神经元之间的连接权重,直至误差减至满足要求为止。反向传播算法的主要特征是中间层能对输出层反传过来的误差进行学习。这种算法不能保证训练期间实现全局误差最小,但可以实现局部误差最小。BP算法在图像处理、语音处理、优化等领域得到应用。

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