片语

muItiIayer perceptron多

modeling perceptron模型感知器

model perceptron模型感知器

perceptron algorithm感知器算法

mlmultilayer perceptron多层感知机

Multilayer Perceptron多层感知器

Perceptron Approach模式识别中感知器算法

polynomial perceptron多项式感知器

perceptron network感知器网络

英汉例句

• There are important differences from the perceptron algorithm.

  这里有一些与感知器算法相区别的重要不同点。

• The continually optimized connecting relation is gained via perceptron and XOR function, then the optimal path graph is found.

  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。

• A method of implementing symbol logic inference system using recurrent multilayer perceptron neural networks is presented in this paper.

  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。

• But what the example illustrates is how a perceptron can weigh up different kinds of evidence in order to make decisions.

  不过这个例子说明的是感知器如何权衡不同种类因素来做出决策的。 并且一个由感知器组成的复杂网络似乎真的可以做出精準的决定。

• A new lattice polynomial perceptron (LPP) model is derived, which is very suitable for VLSI implementation. Computer simulations have been carried out and the experimental results are given.

  导出了便于VLSI实现的多项式感知器的格型实现算法，进行了计算机模拟，并给出了相应的数值结果。

• The perceptron can only solve linearly separable problems.

  感知机只能解决线性可分问题。

• A method of constructing knowledge based fuzzy perceptron based on rough sets theory is proposed.

  提出了用粗糙集理论构造模糊多层感知器的方法。

• It is applicable to any small vocabulary hybrid speech recognition system that combines hidden Markov model (HMM) with multi-layer perceptron (MLP).

  研究适用于隐马尔可夫模型(HMM)结合多层感知器(mlp)的小词汇量混合语音识别系统的一种简化神经网络结构。

• A neural net that USES this rule is known as a perceptron, and this rule is called the perceptron learning rule.

  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。

• The multi-layer perceptron is introduced to charcacterize the microstrip discontinuity by describings-parameters.

  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 quintessential example of a deep learning model is the feedforward deepnetwork or multilayer perceptron (MLP).

  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）。

• Multilayer perceptron networks have been widely used in many applications.

  多层前传神经网络在许多领域有着广泛的应用。

• In this paper, the authors study the detection of signals in non-Gaussian noise, and employ a multilayer perceptron neural network as a detector.

  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。

• Of great interest, popular multilayer perceptron (MLP), radial basis function (RBF) and polynomial neural networks are the focus of the paper.

  其中，对于多层感知器网络、径向基函数网络、多项式网络尤其关注。

• 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.

  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。

• Generally, it is difficult to determine in advance a suitable network structure when a multi layer perceptron neural networks is used for a special fault diagnosis problem.

  一般对特定的基于多层感知器的故障诊断问题，很难确定神经网络的结构。

• After some research I have chosen a multilayer perceptron and standard back-propagation algorithm for training.

  经过我选择了多层感知和标準的反向传播训练算法的研究。

• 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.

  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 separating system consists of a multilayer perceptron (nonlinear part) followed by a linear blind deconvolution (linear part).

  分离系统由多层感知器(非线性部分)后接一个线性盲解卷过程(线性部分)组成。

• The sensitivity analysis approach for the hardware implementation of multilayer perceptron prior to network training is proposed.

  提出了训练前多层感知器硬件设计的灵敏度分析方法。

• Obviously, the perceptron isn't a complete model of human decision-making!

  显然，感知器不是一个人类决策的完整模型！

• Numerical experiments show that the NNKBN model has many advantages over the conventional multi-layer perceptron model.

  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。