发表在“现代生物学”杂志上的一篇神经科学研究论文，破解了这个秘密：他们大脑组织能有效阻断噪声的输入。
According to a neuroscience study published today in Current Biology, they’re blessed with a type of brain activity that may essentially block out noise.
这样神经网络可应用于模式识别的特征提取、聚类分析、边缘检测、信号增强以及噪声抑制、数据压缩等各个环节。
This neural network pattern recognition can be applied to feature extraction, clustering analysis, edge detection, signal enhancement and noise suppression, data compression, such as various links.
其次，提出了电力线噪声信道和多径信道的神经网络优化建模方法。
Secondly, power line noise channel and multi-path channel optimization modeling techniques based on artificial neural network are proposed.
基于自适应噪声对消技术及人工神经网络(ANN)理论，提出了一种谐波电流动态检测方法。
Based on self adaptive noise countervailing method and artificial neural network (ANN) theory, this paper proposes a new approach to the dynamic detecting harmonics.
此外，神经元本身也具有一定的抗噪性，这使得神经元在较小噪声背景下仍能正常工作。
Besides, with smaller noise background, neuron itself is still able to normally work due to its anti-noise property.
基于模糊神经网络算法研究了非线性系统的噪声消除问题，设计了一类非线性自适应逆噪声消除控制器。
Based on Fuzzy Neural Network, the noise canceling problem of the nonlinear system was studied. A type of nonlinear adaptive noise controller was proposed.
实验结果表明，此方法在滤除噪声时具有一般神经网络和中值滤波器所没有的优点，精度明显提高。
The proposed method has obvious advantages over other neural networks and median filter in filtering noise, and the precision of results are much higher.
基于自适应噪声抵消方法和人工神经网络(ANN)理论，提出一种谐波电流检测分析方法。
Based on self adaptive noise countervailing method and artificial neural network (ANN) theory, an approach for harmonics detection and analysis is presented.
利用神经网络来设计自适应噪声抵消系统具有重要的理论意义和实用价值。
The use of neural networks for designing a adaptive noise cancellation system is important theoretical significance and practical value.
提出一种基于人工神经网络(ANN)的噪声品质评价方法。
This paper presents a method of evaluating noise quality based on artificial neural network (ANN).
本文研究了非高斯噪声中信号的检测，采用多层感知器神经网络作为检测器。
In this paper, the authors study the detection of signals in non-Gaussian noise, and employ a multilayer perceptron neural network as a detector.
连续不断地噪声扰得那个妇女神经不安。
目的建立一种新的具有抗噪声能力的神经网络时间序列预测模型。
Aim To construct a new time-series forecasting model based on neural network with the capability of noise immunity.
低强度噪声可引起作业男工神经行为功能的改变。
Changes of neurobehavioral function of male workers could be caused by low intensity noise.
提出了一种用于船舶噪声分类的局域自适应子波神经网络分类方法。
In this paper, an efficient engineering classification of ship noises based on a local adaptive wavelet neural network is presented.
我们观察了神经干细胞系细胞是否可以替代耳蜗内强噪声暴露后所致的细胞缺失。
We examined whether cells from a neural stem cell line could replace cochlear cell types lost after exposure to intense noise.
应用BP神经网络对数字进行识别，其图像的预处理采用去除杂点方法去除噪声，使用逐像素特征提取方法进行特征向量的提取。
Applied BP neural network to recognize Numbers, and adopted a method of wipe off miscellaneous points to take out noise, and used a method of per pix feature extraction to extract feature vector.
与已有的融合方法相比，文章提出的神经数据融合方法具有非偏倚的统计特性而且不需要关于噪声协方差的任何先验知识。
Compared with the existing fusion method, the proposed neural data fusion method has an unbiased statistical property and does not require any prior knowledge about the noise covariance.
利用舰艇声呐实测数据进行网络训练，训练好的神经网络可以对舰艇声呐部位自噪声进行精确预报。
The actual data of naval vessel sonar are used to train the network, and then the trained neural network can forecast the naval vessel sonar self-noise accurately.
将自适应噪声对消技术用于谐波和无功电流检测，提出了一种基于神经网络的自适应检测的新方法。
Using the adaptive noise canceling technology, this paper proposes a new detecting approach of harmonics and reactive currents based on neural networks.
同时，粗糙集对于决策表噪声比较敏感，BP神经网络可以克服这个缺点。
In addition, rough sets is high sensitivity to the noise in the decision table, this weakness can be counterbalance by BP neural network.
讨论了基于自适应模糊神经网络的噪声抵消器的设计方法。
The adaptive Fuzzy Neural Network is employed for adaptive noise cancellation.
自联想神经网络关键在于特征提取和噪声滤波。
The key feature of AANN is feature extract and noise filtering.
计算机模拟表明，在加性高斯噪声下，使用该神经网络可以达到最大似然译码。
The computer simulation shows that the decoder can achieve maximum likelihood decoding in the environmemts of additive white Gaussian noise.
提出了一种基于人工神经网络的含噪声文字的识别方法。
In this paper, a method of the Neural Network is proposed for the word recognition.
针对拉萨市道路交通噪声污染问题，运用人工神经网络理论和方法对拉萨市道路交通噪声的等效连续声级进行预测。
Aiming at the traffic noise problem of Lhasa, the author USES artificial neural network theory and method to predict the equivalent consecutive sound level of traffic noise in Lhasa.
软件失效预测中的一个普遍的问题是数据中存在噪声，而神经网络具有鲁棒性并对噪声有很强的抑制能力。
A common problem in software faults prediction is the presence of noise in the data. Neural Networks are robust and have a good noise tolerance.
传统的神经网络非均匀性校正算法对噪声具有较好的自适应性，但当空间低频噪声较大时，校正效果明显下降。
The traditional neural network correction has a good adaptivity to the noise. But with a stronger low frequency space noise, the correction effect is very poor.
本文首先引入一个能方便进行在线自适应的扩展控制对象自适应神经网络模型，在此基础上提出一种噪声有源控制的自适应神经网络方法。
This paper firstly introduces an extended plant adaptive neural network model which can be on-line adapted conveniently, then presents a method of active noise control using adaptive neural networks.
在有噪声的情况下，弱的信号可以使神经元产生发放。
In the presence of noise, the neuron produces firing with small signal.
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