| 1. | An image compressing algorithm based on pca sofm hybrid neural network
混合神经网络的图象压缩算法 |
| 2. | Development of a car - following model based on combined neural network model
混合神经网络跟驰模型的建立 |
| 3. | Research on mixture neural network model based on radial basis function
基于径向基函数的混合神经网络模型研究 |
| 4. | A simple and effective fuzzy identification approach is presented
摘要提出一种简明而有效的基于混合神经网络的模糊辨识方法。 |
| 5. | Application of generalized hybrid neural network modeling methods in penicilllin fermentation process
混合神经网络建模方法在青霉素发酵过程中的应用 |
| 6. | In this research background , this paper come up with a ftc method based on the hybrid neural network and apply hi the ship automatic manoeuvre system
本文就是在这样的研究背景下，运用集成智能技术，提出一种基于混合神经网络的容错控制方法，并应用于船舶控制系统。 |
| 7. | Simulation results show that this fuzzy neural networks ( fnn ) has better generalization and approximation abilities . 3 . it is compared the three kinds of multi - resolution neural networks ( mrnn )
针对目前发酵过程应用的混合神经网络模型做了比较，串连型和串并联型混合神经网络训练复杂，许多成熟的训练方法不能采用。 |
| 8. | The training of the multi - resolution neural networks in parallel is simple . but the generalization ability is bad compared to the other multi - resolution neural networks . so we use the multi - resolution fuzzy neural networks model
并联混合神经网络训练方法简单，但泛化能力不强，因此，本文采用anfis的混合模糊神经网络模型，与并联的混合神经网络相比，其泛化能力和建模精度都有了提高。 |
| 9. | The principle research contents include : ( 1 ) this paper comes up with a new ftc scheme based on the hybrid neural network , which is focused on the sensor failure and actuator failure , thus make use of multi - neural network to realize the fault detection and fault tolerant control of the system
主要研究内容包括： ( 1 )提出了一种新的基于混合神经网络的容错控制系统框架结构，针对传感器和执行器两类故障，应用多种类型神经网络实现系统的故障检测与容错控制。 |
| 10. | In view of the feature of neural network and its advantages in pattern recognition , we have a great deal work in off - line handwritten character recognition based on neural network . we present two recognition methods based on neural network . one of which is the hybrid neural network recognition system , a multi - level neural network classifier constructed by using the multi neural networks integration technology
由于神经网络的特点及其在手写体字符识别领域体现出的潜力，本文对基于神经网络的手写体字符识别技术进行了大量的研究工作，提出了两种新颖的基于神经网络的手写体字符识别模型，其中，基于混合神经网络的手写体字符识别模型利用了在抗干扰和描述字符拓扑结构方面具有互补性的中心投影特征和llf特征，使用多神经网络集成技术构建了多级的神经网络分类器。 |
