| 1. | The study of fuzzy identification theory and its practical applications
模糊辨识理论与应用研究发展 |
| 2. | Ann based on trend identify and the application in hydrological time series forecast
基于趋势辨识理论的神经网络及其在水文时间序列预报中的应用 |
| 3. | The theory of fuzzy neural network ( fnn ) modeling for nonlinear systems is presented
摘要论述了模糊系统和神经网络相结合的非线性系统辨识理论。 |
| 4. | Modeling and classification of two - channel elctromyography signals based on blind channel identification theory
基于盲辨识理论的双通道肌电信号建模与分类 |
| 5. | The proposed methods can be used as data preparation techniques to detect bad data and fill the blank with a more accuracy value in an initial series . the modeling accuracy of grey system is greatly improved by such methods
2 、针对序列中含有空穴或不良数据的情况，将参数估计与不良数据辨识理论作为数据预处理技术应用于灰色系统建模，使得模型预测结果更为精确。 |
| 6. | The theoretical background of the test signal method is the theory of mechanical admittance and mode identification , which is based on the frequency scanning of the test signal and has already been used widely in mechanical engineering
提出了一种基于测试信号的小扰动稳定性分析方法?测试信号法，用于分析电力系统低频振荡问题。其理论基础是机械导纳理论和模态辨识理论。 |
| 7. | However , with the development of society and science , nonlinear system is more and more important . the conflict between control and model is getting more and more evident . this fact results in the development of nonlinear system identification theory
但随着社会、科学的发展,非线性系统越来越受到人们的关注,其控制与模型之间的矛盾越来越明显,因而非线性系统的辨识问题也越来越受到重视,其辨识理论不断发展和完善。 |
| 8. | Based on the theory of system identification and experimental data , the simulating results of many kinds of parameter models have been compared . among them , we can find a parameter model that can precisely express the dynamic character of measurement system . on the system model constructed , the dynamic error of measuring data is processed by inverse filtering method
本文先后对测试系统进行了多次动态校准，根据所得实验数据在系统辨识理论的基础上，比较了多种参数模型的仿真效果，寻找到一类能够准确地描述测试系统动态特性的参数化模型，并根据所建立的系统模型，采用反滤波方法改进了测试系统的动态特性。 |
| 9. | There are lots of non - linear systems in the nature . because classical and morden control methods have common limitation : mathematical model of the plant has to be known in advance . but in fact many plants are intricate uncentaintied and time - varying . in addition , they also are non - linear . though there are methods of system identification in control theories , the identification theories and ways of non - linear and time - varying system are not mature and systematic . it is very difficult to carry out effective real - time control . the neural networks can approximate random non - linear relations and study by itself , and it provides new thoughts and new ways for solving these problems
由于经典和现代控制方法存在一个共同的局限性：就是要求预先知道被控对象的数学模型，但实际上许多对象具有复杂的不确定性和时变性；此外还具有复杂的非线性。虽然在控制理论中有系统辨识的手段，但是对于非线性时变系统尚无成熟的和系统的辨识理论与方法，要实行有效的实时控制就很难了。人工神经元网络有表示任意非线性关系和自学习等能力，给解决这些问题提供了新思想和新方法。 |
| 10. | E . tva load model structure , which is more adaptive to the measurement - based load modeling . based on the presented model , the dissertation further researches and applies the least square algorithm in classic system identification theory as well as the simplex method and the genetic algorithm in modern system identification theory to identify the load model
在广泛研究现有典型负荷模型结构的基础上，论文提出了适用于量测建模的时变适应的负荷模型( tva负荷模型) ；进而研究并综合应用传统辨识理论中的最小二乘辨识法和现代辨识理论中的单纯形法、遗传算法进行负荷模型辨识。 |
