Compared with artificial neural networks, realistic neural networks are much closer to real biological neural networks.
现实性神经网络是相对人工神经网络而言的，它与人工神经网络相比，更接近真实的生物神经网络。
Indeed, the names of major subfields of computer science-such as artificial neural networks, genetic algorithms, and evolutionary computation-attest to the influence of biological analogies.
说实话，在计算机科学的一些主要分支学科的命名上就可以看出生物学的影子，譬如人工神经网络，遗传算法和进化计算法等等。
We now have computer viruses, neural networks, Biosphere 2, gene therapy, and smart CARDS — all humanly constructed artifacts that bind mechanical and biological processes.
而今我们有了电脑病毒，神经网络，生物圈二号，基因治疗法以及智能卡——所有这些人工构造的产品，联接起了机械与生物过程。
The International Neural Network Society promotes the understanding of biological and artificial neural networks.
国际神经网路协会致力于加深对生物和人工神经网路的认识。
The planar delay differential system (1) has significant biological and physical backgrounds. For example, some special cases of (1) have been proposed as models of neural networks.
平面系统（1）具有重要的生物和物理背景，大量的神经网络模型都是以这种形式被提出的。
My current research interests include theory of delay differential equations and reaction-diffusion equations and also their application to neural networks and biological dynamic systems.
研究方向包括时滞微分方程和反应扩散方程理论及其在神经网络和生物动力系统方面的应用。
Real biological data experiments have shown that this classification method outperformed than single neural networks, 1-nearest-neighbor classifiers and decision trees.
实际的生物学数据实验表明该方法性能优于单个神经网络，最近邻法和决策树。
According to the principle of biological neuron, which state influences the condition of the brain, a new method is presented to adaptively construct neural networks.
该文根据生物神经元状态变化导致人脑空间结构和状态变化这一原理，提出了一种自适应构造神经网络的新方法。
However, neural networks have a strong similarity to the biological brain and therefore a great deal of the terminology is borrowed from neuroscience.
然而，神经网络与大脑有很大的相似性，因此从神经科学中借用了大量的术语。
The study on internal behaviors of ANN is meaningful for the understanding of both biological and artificial neural networks.
人工神经网络（ANN）内部行为的研究，无论是对生物神经系统内部工作机理、ANN理论，还是对ANN应用都有重要意义。
The study on internal behaviors of ANN is meaningful for the understanding of both biological and artificial neural networks.
人工神经网络（ANN）内部行为的研究，无论是对生物神经系统内部工作机理、ANN理论，还是对ANN应用都有重要意义。
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