Performance Analysis of A Feed-Forward Artifical Neural Network With Small-World Topology
نویسندگان
چکیده
منابع مشابه
A Multilayer Feed Forward Small-World Neural Network Controller and Its Application on Electrohydraulic Actuation System
Being difficult to attain the precise mathematical models, traditional control methods such as proportional integral (PI) and proportional integral differentiation (PID) cannot meet the demands for real time and robustness when applied in some nonlinear systems.The neural network controller is a good replacement to overcome these shortcomings. However, the performance of neural network controll...
متن کاملSignal Prediction by Layered Feed - Forward Neural Network (RESEARCH NOTE).
In this paper a nonparametric neural network (NN) technique for prediction of future values of a signal based on its past history is presented. This approach bypasses modeling, identification, and parameter estimation phases that are required by conventional parametric techniques. A multi-layer feed forward NN is employed. It develops an internal model of the signal through a training operation...
متن کاملFeed forward neural network entities
Feed Forward Neural Networks (FFNNs) are computational techniques inspired by the physiology of the brain and used in the approximation of general mappings from one nite dimensional space to another. They present a practical application of the theoretical resolution of Hilbert's 13 th problem by Kolmogorov and Lorenz, and have been used with success in a variety of applications. However, as the...
متن کاملResponse analysis of feed-forward neural network predictors
In this paper, we investigate the characteristics of some one-step-ahead nonlinear predictors based on a two-layer feed-forward neural network (2LFNN). The behavior of neural networks (NN) is investigated in the frequency domain using two frequency response estimation techniques, and in the time domain, by analyzing the unit step and triangular pulse responses. Some of the estimated frequency r...
متن کاملMax-Entropy Feed-Forward Clustering Neural Network
The outputs of non-linear feed-forward neural network are positive, which could be treated as probability when they are normalized to one. If we take Entropy-Based Principle into consideration, the outputs for each sample could be represented as the distribution of this sample for different clusters. Entropy-Based Principle is the principle with which we could estimate the unknown distribution ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Procedia Technology
سال: 2012
ISSN: 2212-0173
DOI: 10.1016/j.protcy.2012.02.062