阐述了混沌学习算法的机理，设计了交通流量WNN混沌时间序列自适应学习算法。
Then the mechanism of the chaotic learning algorithm is described, and the adaptive learning algorithm of WNN for traffic flow time series is designed.
特别是对阈值去噪方法，提出了一种基于正交小波变换和自适应学习算法的噪声抑制方法。
Especially to threshold de-noising, a method based on orthogonal wavelet analysis and self-adaptive learning algorithm was proposed here.
提出了一种基于神经元状态融合的组合导航系统信息融合模型，给出了神经元融合权重在线自适应学习算法。
An information fusion model of integrated navigation system based on neurons is proposed, and also an on line adaptive training algorithm of the weights of neuron is given.
通过利用合理的学习算法进行训练，神经网络对事物和环境具有很强的自学习、自适应和自组织能力。
Carries on the training through the use reasonable study algorithm, the neural network has to the thing and the environment very strong from the study, auto-adapted and from the organization ability.
通过自适应的离散粒子群算法来对核相似矩阵进行学习。
Uses the adaptive discrete particle swarm algorithm to learn the similar kernel matrix.
本文对自适应算法以及智能天线等技术进行了研究学习，并选取功率谱倒置算法进行了FPGA的设计实现。
This thesis studies adaptive algorithms and smart antenna, and selects the power spectrum inversion method to implement with FPGA.
针对BP神经网络的缺点，研究了一种动态自适应调整学习参数的改进型BP算法。
To BP neural shortcoming of network, study one dynamic self-adaptation is it study improvement type BP algorithm of parameter to adjust.
在反馈学习算法的基础上，将模糊逻辑和神经网络自适应控制的结构结合在一起。
The neural network-based adaptive control and fuzzy logic are integrated based on feedback learning algorithm.
结果表明，该算法具有更快的训练学习速度和良好的数据自适应能力。
It turns out that the algorithm can train studying-speed faster and it is of good self-adaptation to data.
提出将IRT的相关算法应用于在线教学系统，通过相应的算法，实现自适应学习管理和跟踪。
The paper proposes an online teaching system based on IRT, and by this system, the managing and tracing process of adaptive learning are realized.
该方法采用增量学习的思想，对话题追踪任务中的自适应学习机制提出了新的算法。
This method adopts the idea of increment learning, and presents new algorithm to the adaptive learning mechanism in the task of topic tracking.
最后，论文给出了基于该知识模型的自适应知识点推荐和个性化学习页面生成的算法设计和实现结果。
At last, this paper gives the arithmetic design and the realization of the self-adaptive knowledge recommendation and individually learning pages compose.
使用自适应学习率的算法调整网络的权值，加快了网络的学习速度。
Using an algorithms of adaptive learning rates adjust the network's weight for quickening learning rates.
与标准BP算法比较，该系统通过结合附加动量法和自适应学习速率形成新的BP改进算法。
Compared to the standard BP, this algorithm integrated the additional momentum method with the adaptive learning rate method.
该方法采用增量学习的思想，对话题追踪任务中的自适应学习机制提出了新的算法。
Based on the idea of increment learning, the paper presents a new algorithm for the adaptive learning mechanism in the task of topic tracking.
提出的自适应粒子群优化算法，用于优化多层前馈神经网络的拓扑结构，提高了神经网络的学习质量和速度。
The structure of multi-layer feedback forward neural network is optimized by improved PSO. Learning quality and training speed of the neural network are improved.
为了对在线学习文档进行分类，本文根据自适应谐振理论给出了一个半监督学习模糊art模型(SLFART)及其算法。
For learning document classification on line, the paper gives the semi-supervised learning fuzzy ART model (SLFART) based on adaptive resonance theory and the models algorithm.
在网络算法上，提出一种自适应的BP算法，该方法能有效的抑制网络陷于局部极小并缩短了学习时间。
About algorithm, the paper has presented a self-adaptive error BP algorithm which can prevent the networks from getting in the part least and can shorten the studying time.
本文提出了一种改进的BP算法，该算法基于黄金分割法自适应调整网络学习速率。
This paper presents an improved BP algorithm, which can adapt learning rate using gold-segmentation.
在个人信用评估部分中，对所有的离散数据进行量化处理，然后使用局部学习率自适应算法，对BP算法加以改进。
In the individual credit evaluation part, it quantifies all kinds of scattered data, and to improve BP algorithm it USES local self-adaptive study rate algorithm.
首先阐述了CMAC神经网络的原理、结构和学习算法，提出了一种新的采用竞争学习原理的非等距自适应量化算法。
We first discuss the structure and principle of the CMAC neural network. Using competitive learning, we develop a new adaptive quantization algorithm.
提出一种基于区域自适应学习的人脸图像超分辨率复原算法。
A novel region adaptive learning-based super resolution algorithm for human face images is proposed, which divides a face image into flat regions and detailed regions.
针对包装印刷传动位置伺服系统，介绍一种基于共轭梯度学习算法的神经网络自适应PID控制方法。
The paper proposes an adaptive neural network PID controller based on weighlearning algorithm using the gradient descent method for the AC position servosystem of binding and printing.
并对该神经网络模型的学习算法进行了研究，提出了一种自适应并行学习算法。
The learning of the network is also studied and an adaptive parallel learning algorithm is proposed.
提出了基于改进的BP神经网络学习算法和自适应残差补偿算法的炼铜转炉吹炼终点组合预报模型。
It is the first time that a converting furnace endpoint prediction model based on an improved BP neural network and error compensation of linear regression.
文中基于块增量学习和逆学习过程，提出了自适应迭代回归算法。
This paper presents an adaptive and iterative support vector machine regression algorithm (CAISVR) based on chunking incremental learning and decremental learning procedures.
并针对某些学习应用提出了一种两阶段自适应控制逐一训练算法。
Using this algorithm, an adaptive learning controlling value is established according to the recent convergence error and its rate of change.
并针对某些学习应用提出了一种两阶段自适应控制逐一训练算法。
Using this algorithm, an adaptive learning controlling value is established according to the recent convergence error and its rate of change.
应用推荐