多值指数关联联想记忆模型（MMECAM）是一种高存储容量的自联想记忆神经网络。
Modified Multi-valued Exponential Correlation Associative Memory Model (MMECAM) is a neural network with higher storage capacity.
本文利用模糊联想记忆神经网络作为控制器，对任意初始状态的结构自由振动进行主动控制。
The active control of structural free vibration using fuzzy associative memory networks controller is studied in this paper.
本文提出一种基于模糊联想记忆神经网络的土地质量评价方法，并以实例证实了该方法的简便、快速、客观和实用性。
Now a land quality evaluation method based on fuzzy association neural network is put forward and the method is proved simple, rapid and practical.
RF的神经网络与调节我们如何去思考与记忆的大脑皮层相连接。
The RF's neural networks link up with the cerebral cortex, which regulates how we think and remember.
利用图像处理技术将测井曲线和地质参数转化为图像模式，由神经网络自动提取和记忆曲线所表征的小层模式特征。
Logging curves and stratum parameters are changed to image pattern by image process technology. Neural networks are introduced to extract and remember pattern character of curves automatically.
同时，应用神经网络的学习和记忆功能，对控制变量的隶属函数和控制规则进行优化，使控制方案更趋于合理。
At the same time, using the study and memory ability of neural networks, optimize subject function and control rules of control variables, which makes the control scheme more reasonable.
阐明了神经网络具有记忆、学习功能，得出它能够很好模拟物流发展趋势。
Because of neural networks? Function of learn, memory, it can simulate the tendency of logistics development.
神经网络具有良好的记忆、归纳和学习能力，对难以用数学方法建立精确模型的信息、工艺等能够进行有效地预测建模。
The neural network has the abilities of memory, induction & study , it can effectively build forecasting model for information & technics which are difficult to be built into an exact math model.
基于神经网络自联想记忆功能，提出了一种新的数字图像水印算法。
A novel digital image watermarking algorithm based on the association memory ability of neural network is proposed in this paper.
其中一个方面体现在人脑的抽象处理与记忆能力与现有人工神经网络有很大的不同。
The abstract embodying in the human brain handles a aspect among them and remembers that the ability is very big different from now available artificial neural networks.
提出了将一种改进的人工神经网络联想记忆模型应用于计算机数控机床的故障诊断方法。
A modified associative memory model of Artificial Neural Network (ANN) is introduced into the fault diagnosis of computer numerical control machine tool.
神经网络计算机能模拟人脑的并行处理方式，具有惊人的自学习、思维、推理、判断和记忆的功能。
Neutral network computer can simulate human brains in parallel information processing manner, with functions of striking self-learning, thinking, reasoning, judging, and memorizing.
将一种改进了的神经网络联想记忆模型应用于雷达伺服分系统的BIT设计中，取得了比较满意的效果。
A new model of neural network associative memory is introduced into the BIT design of radar servo sub-system, which achieves satisfactory effect.
最后对抑制型动态突触神经网络在联想记忆中的应用进行了研究。
Finally, we apply neural network models with dynamic depressing synapses in the field of associative memory.
讨论了一种模糊神经网络实现记忆的条件和记忆的特点，并给出了样本组格子点分布的概念。
The condition for a fuzzy neural network to realize memory is discussed, and the concept of lattice point is given.
在此基础上，应用混沌神经网络对异步电动机鼠笼转子断条故障进行动态记忆和恢复。
In the paper faults of three phase induction motors with broken bare is diagnsed usingdrpamic associative memory of chaotic neural network.
已有的研究结果表明，混沌神经网络在求解复杂优化问题和联想记忆等方面比现有网络有着更好的性能。
The research results show that the chaotic neural networks are more effective than other existing neural networks to solve associative memory and complex optimization problems.
神经网络的联想记忆功能、容错性和鲁棒性以及很好的非线性映射能力，使得这一方法明显优于传统的诊断方法。
The associational memory function, error-correction, robustness and the well non-linear reflection ability make the proposed method superior to the traditional dictionary method apparently.
稳定点是决定人工神经网络联想记忆能力的最重要因素。
The number of stable points is a key measurement of the capacity of neural network"s associative memory."
本文较为详细地探讨了神经网络双向联想记忆法在机械系统故障诊断中的应用。
This paper studies in details the application of the bidirectional associative memory method to the fault diagnosis of mechanical system.
反馈神经网络是神经网络中最重要的类型之一，这种网络的突出特点就是它具有联想记忆的功能。
Feedback neural network is one of the most important neural network, the most remarkable feature of this kind of network is the associative memory function.
联结主义认为使用单一机制的神经网络系统足以解释规则和不规则语素变体； 双机制则认为需要规则系统和联想记忆两个不同的机制对此进行解释。
On the other side of the debate are dual-mechanism approaches which posit that regular verb forms are computed in a rule-processing system while irregular verbs are processed in associative memory.
由于这类神经网络能存储双极向量对，并在模式识别、联想记忆、人工智能等方面有广泛应用，对这类模型的研究引起很多学者的关注。
The class of networks has wide applications in many fields such as pattern recognition, associative memory and artificial intelligence. Such model caused much attention of researchers.
根据采集的样本训练出模糊神经网络的连接矩阵，然后对单个的联想记忆网络进行合成，实现故障的诊断。
The gathered samples are used to train the connected matrix of the fuzzy-neural network. And every single fuzzy-neural network is assembled to realize fault diagnosis.
作为仿生神经元数学模型，随机神经网络在联想记忆、图像处理、组合优化问题上都显示出较强的优势。
As a biological neural mathematical model, RNN has particular advantages of associative memory, image processing and combinatorial optimization.
研究结果表明，基于混沌神经网络的故障诊断有助于故障模式的记忆和重视。
Diagnose result suggest that the chaotic neural network is beneficial to dynamic memory retrieval and faults identification. And chaotic neural network has fault tolerance.
研究结果表明，基于混沌神经网络的故障诊断有助于故障模式的记忆和重视。
Diagnose result suggest that the chaotic neural network is beneficial to dynamic memory retrieval and faults identification. And chaotic neural network has fault tolerance.
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