Neural Network Modeling and Identification of Dynamical Systems
暫譯: 神經網絡建模與動態系統識別

Tiumentsev, Yury, Egorchev, Mikhail

商品描述

Neural Network Modeling and Identification of Dynamical Systems presents a new approach on how to obtain the adaptive neural network models for complex systems that are typically found in real-world applications. The book introduces the theoretical knowledge available for the modeled system into the purely empirical black box model, thereby converting the model to the gray box category. This approach significantly reduces the dimension of the resulting model and the required size of the training set. This book offers solutions for identifying controlled dynamical systems, as well as identifying characteristics of such systems, in particular, the aerodynamic characteristics of aircraft.

  • Covers both types of dynamic neural networks (black box and gray box) including their structure, synthesis and training
  • Offers application examples of dynamic neural network technologies, primarily related to aircraft
  • Provides an overview of recent achievements and future needs in this area

商品描述(中文翻譯)

《神經網路建模與動態系統識別》提出了一種新的方法,用於獲得適應性神經網路模型,以應對在現實應用中通常出現的複雜系統。本書將可用於建模系統的理論知識引入純粹的經驗黑箱模型,從而將模型轉換為灰箱類別。這種方法顯著減少了所得到模型的維度以及所需的訓練集大小。本書提供了識別受控動態系統的解決方案,以及識別此類系統特徵的方案,特別是飛機的空氣動力學特徵。

- 涵蓋兩種類型的動態神經網路(黑箱和灰箱),包括其結構、合成和訓練
- 提供動態神經網路技術的應用範例,主要與飛機相關
- 提供該領域近期成就和未來需求的概述