It stresses that language input and output is a complete process of language learning, which is inseparable.
语言的输入和输出是相互依存的一个整体，是语言学习的完整过程。
This article describes a new type of fuzzy system with interpolating capability to extract MISO fuzzy rules from input output sample data through learning.
描述了一个通过学习从输入输出采样数据中提取MISO模糊规则的具有插值性能的新型模糊系统。
Language learning is an integrated process of the input and the output of language.
语言的学习是语言输入和语言输出相互结合和相互作用的过程。
It established the model's output mathematic function and learning algorithm. Computer simulations showed the equivalence of fuzzy chaos neural network model and the original chaotic system.
确定了模型的输出函数，并推导了模型的学习算法，仿真结果表明永磁同步电机的模糊混沌神经网络模型与原系统是等价的。
The results show that this algorithm can model input and output learning kernel of dynamic nonlinear system quickly, which is superior to other learning methods of wavelet network.
结果表明该算法能够对动态非线性系统的输入输出快速学习和建模，优于其它小波网络的学习算法。
The model may solve a kind of problems of synthetic evaluation by determining standard objects, processing data normally, network adaptive learning and evaluation result output.
该模型通过确定标准对象，数据的标准化处理，网络自适应学习和评价结果输出等环节，可以有效地解决一类综合评价问题。
If the initial value is not the expected output, but in its certain neighborhood, then we put such questions as the initial value of iterative learning control.
如果不在期望输出上，而是在期望输出轨迹的某一邻域上，我们把这类问题称为迭代学习控制的初值问题。
It get the nonlinear mapping to describe the relation of the system's input and output by learning the controlled system's input and output data.
它依据被控系统的输入输出数据，通过学习得到一个描述系统输入输出关系的非线性映射。
The actual output trajectory of the system achieved better convergence to the desired trajectory by using the iterative learning control algorithm.
利用该算法进行学习控制，使系统的实际输出能更好地收敛于系统的理想输出。
Therefore, it plays a critical role in the process of language teaching and learning. And it has a direct effect on learner output.
因此，它在组织课堂教学和学习者语言习得过程中起着至关重要的作用，直接影响着学习者的语言输出。
Artificial neural network was used widely because of its self organizing and self learning, much input and much output ability.
人工神经网络由于其具有较好的自组织、自学习，多输入、多输出的能力，在预测方面已取得了广泛应用。
The good localization characteristics of wavelet functions in both time and frequency space allowed hierarchical multi-resolution learning of input-output data mapping.
利用小波变换所具有的良好的时频分析特性，实现了输入输出之间映射关系的多分辨学习。
Spectrum analysis diagnosis system (SADS) is composed of user interface, data management, KBM, reasoning facility, self-learning adjusting, remote fault diagnosis and system output modules etc.
油液光谱分析诊断系统(SADS)由人机交互、数据管理、知识库管理、推理机、自学习调整、远程故障诊断和系统输出等模块组成。
An adaptive iterative learning control approach is proposed for a class of single input, single output uncertain nonlinear systems with completely unknown high frequency learning gain.
针对一类单输入单输出不确定非线性重复跟踪系统，提出一种基于完全未知高频反馈增益的自适应迭代学习控制。
Language learning needs lots of practices, which include mechanical drills, meaningful exercises, output training as well as variety of interactions.
语言学习需要大量练习，既有机械性的练习，也包含各种有意义的练习；
The big limitation of deep learning is that almost all the value it's creating is in these input-output mappings.
深度学习所面临的一个重要限制是，其创造的几乎所有价值都在输入-输出映射当中。
The model sheds light on the implementation of an explicit learning approach by integrating the two factors with input and output in classroom learning.
这样，这个模式处于一个整体循环中，保持了课堂教学中的输入和输出的平衡。 毫无疑问，显性学习方式将是中国大学生学习外语的重要方式。
The good localization characteristics of wavelet functions in both time and frequency space allow hierarchical multi-resolution learning of input-output data mapping.
由于小波变换在时间和频率空间具有良好的定位特性，使小波神经网络可对输入、输出数据进行多分辨的学习训练。
Learning technical movements is also an application of input, transformation, processing analysis, storage and output of information.
人们对技术动作的学习也是一和信息的输入、转换、加工分析、贮存和提取运用的过程。
The learning method of hidden-output layer weights is the steepest descent method and the one of input-hidden layer weights is genetic algorithm(GA) .
网络隐层-输出层的权值采取最速下降法学习，输入层-隐层的权值采用遗传算法进行学习；
The learning method of hidden-output layer weights is the steepest descent method and the one of input-hidden layer weights is genetic algorithm(GA) .
网络隐层-输出层的权值采取最速下降法学习，输入层-隐层的权值采用遗传算法进行学习；
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