| 1. | Finite element approach for structural dynamic analysis using generalized eigenvalue - based neurocomputing
有限元结构动力分析的广义特征值的神经计算 |
| 2. | In the last chapter , a neural computing algorithm for bit rate control is designed
在本文最后一章里，提出一种利用神经计算进行视频输出码率控制的算法。 |
| 3. | The simulation result shows that the quantum neuron network is superior to classical bp and rbf network for the financial data analysis example
仿真结果显示，就算例而言，该量子神经计算网络的性能优于传统的神经网络。 |
| 4. | The innovation of the thesis as follows : advances the generalized computing theory that combines symbolic computing with neural computing , fuzzy computing and evolutionary computing
本文的价值在于：提出了融符号计算、神经计算、模糊计算和演化计算于一体的广义计算理论。 |
| 5. | Exploration of the convergence of theoretical work and experimental data on neuronal computations that highlight the feedback requirement for the systematic operation of the nervous system
集中探讨了神经计算科学的理论工作和实验数据，特别讨论了神经系统进行系统性运作时反馈的必要性。 |
| 6. | A novel quantum neural computational model is constructed based on the universal quantum gates unit ( i . e . phase - shift gate and controlled not gate ) , which acts as the basic computational component
研究以通用量子逻辑门组(即相移门和受控非门)作为计算基函数，构造新的量子神经计算网络模型。 |
| 7. | The training of a particular neural network involves huge amount of data . to improve the speed of computation , we used the idea of grid computing to construct a distributed system
但是因为神经计算处理的数据比较庞大，所以为了提高运算速度，我们引进了网格计算( gridcomputing )的结构思想，架构一个分布式系统。 |
| 8. | In the engineering application of ci , two methods of evolutionary computing and neural computing the fourier factors are proposed which redound to the application of fourier transformation to the engineering
在计算智能的工程应用方面，本文提出了fourier系数的进化计算和神经计算两种智能计算方法，为fourier变换的工程应用提供了方便。 |
| 9. | Our ann model runs on a neuron computing platform witch is based on grid technology , and it has powerful computing ability , also , it allows users to design their own ann prediction model conveniently to match their specified needs
我们的模型应用在一个基于网格的神经计算平台之上，它可以给用户提供强大的计算能力，并能让用户按照他们的需求方便地定制他们自己的神经网络预测模型。 |
| 10. | The fuzzy system is constructed through the artificial neural learning algorithm . third , the fault diagnosis using neural networks is discussed in this paper , especially the internal backward neural network with deviation elements . its model and learning algorithm are showed in detail
其中详细讨论了带有偏差单元的递归神经网络的模型和学习算法，在此基础上合成了模糊神经网络系统，将模糊理论和神经计算原理相结合，使神经网络借助其大规模的并行分布处理结构完成模糊诊断的推理过程。 |
