这里有一些与感知器算法相区别的重要不同点。
There are important differences from the perceptron algorithm.
风速的反演是基于多层感知器网络;
The network for retrieving wind speed is a multi-layer perceptron.
安装abs感知器线到支架。
如果配备有油面感知器,断开感知器。
If equipped with an oil level sensor, disconnect the sensor.
拆下电线防护壳和感知器。
一个等待元件,它将等待触摸感知器被按下的那一刻。
电池温度感知器输入电压低于可接受范围。
Battery temperature sensor input voltage below an acceptable range.
提出了一种单层感知器网络训练的新算法。
A new algorithm is proposed for training single layered perception neural networks.
显然,感知器不是一个人类决策的完整模型!
Obviously, the perceptron isn't a complete model of human decision-making!
感知器以一种不同的而且可能更为直观的方式来使用权重。
A perceptron utilizes weights in a different and perhaps more intuitive way.
清洗器存储箱、填注口盖和感知器都可以维修。
The washer reservoir, filler cap, and sensor are each available for service.
这可能是因为有些人没有产生特定感知器的基因。
This may be because some people do not have the genes necessary to generate particular smell recepters in the nose.
使用感知器准则对给定的两个样本进行分类器设计。
Guidelines for the use of sensor for a given classification in two samples of design.
Lego系统能够被很容易地添加额外的感知器、发动机和催化剂。
The Lego system can be easily extended with additional sensors, motors, and activators.
本文采用多层感知器建立了微带不连续性的神经网络模型。
The multi-layer perceptron is introduced to charcacterize the microstrip discontinuity by describings-parameters.
本文研究神经网络的多层感知器模型在语音识别中的应用。
This paper describes the use of multi-layer perception model of neural network in speech recognition.
这些感知器实际上就是一些感知气味和传送信息给大脑的细胞。
These recepters are the cells which sense smell and send messages to the brain.
本文研究在MATLAB环境下,利用感知器求解逻辑分类问题。
In this article we investigate logic classification problems that are solved using perceptrons on MATLAB condition.
介绍一种用循环多层感知器神经网络实现符号逻辑推理系统的方法。
A method of implementing symbol logic inference system using recurrent multilayer perceptron neural networks is presented in this paper.
一个使用这个规则的神经网络称为感知器,并且这个规则被称为感知器学习规则。
A neural net that USES this rule is known as a perceptron, and this rule is called the perceptron learning rule.
数值实验表明NNKBN模型在许多方面优于传统的多层感知器模型。
Numerical experiments show that the NNKBN model has many advantages over the conventional multi-layer perceptron model.
感知器是一种有用的神经网络模型,可以对线性可分的模式进行正确分类。
Perceptron is a kind of useful neural network model and can classify the classification of the detachable linearity correctly.
现在,如果true函数是布尔或,那么感知器将从三个训练实例中归纳出所有的实例。
Now, if the true function were Boolean or, then the perceptron would have correctly generalized from three training instances to the full set of instances.
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.
深度学习模型的一个典型例子是前馈深度网络,或者说多层感知器(MLP)。
The quintessential example of a deep learning model is the feedforward deepnetwork or multilayer perceptron (MLP).
感知器培训规则是基于这样一种思路—权系数的调整是由目标和输出的差分方程表达式决定。
The perceptron training rule is based on the idea that weight modification is best determined by some fraction of the difference between target and output.
利用感知器异或函数获得了节点之间不断优化的连接关系,然后得到最优路径图。
The continually optimized connecting relation is gained via perceptron and XOR function, then the optimal path graph is found.
有了地震感知器,这些都将不会发生。短短的15秒就足以打开门并运出消防设备。
With QuakeGuard, this would not have happened because in as little as 15 seconds the doors could be opened and the engines driven outside.
有了地震感知器,这些都将不会发生。短短的15秒就足以打开门并运出消防设备。
With QuakeGuard, this would not have happened because in as little as 15 seconds the doors could be opened and the engines driven outside.
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