A Pyramidal Neural Network For Visual Pattern Recognition
نویسندگان
چکیده
منابع مشابه
AN IMPROVED CONTROLLED CHAOTIC NEURAL NETWORK FOR PATTERN RECOGNITION
A sigmoid function is necessary for creation a chaotic neural network (CNN). In this paper, a new function for CNN is proposed that it can increase the speed of convergence. In the proposed method, we use a novel signal for controlling chaos. Both the theory analysis and computer simulation results show that the performance of CNN can be improved remarkably by using our method. By means of this...
متن کاملMembrain Neural Network for Visual Pattern Recognition
Recognition of visual patterns is one of significant applications of Artificial Neural Networks, which partially emulate human thinking in the domain of artificial intelligence. In the paper, a simplified neural approach to recognition of visual patterns is portrayed and discussed. This paper is dedicated for investigators in visual patterns recognition, Artificial Neural Networking and related...
متن کاملan improved controlled chaotic neural network for pattern recognition
a sigmoid function is necessary for creation a chaotic neural network (cnn). in this paper, a new function for cnn is proposed that it can increase the speed of convergence. in the proposed method, we use a novel signal for controlling chaos. both the theory analysis and computer simulation results show that the performance of cnn can be improved remarkably by using our method. by means of this...
متن کاملNeocognitron: A hierarchical neural network capable of visual pattern recognition
-A neural network model for visual pattern recognition, called the "neocognitron, "' was previously proposed by the author In this paper, we discuss the mechanism of the model in detail. In order to demonstrate the ability of the neocognitron, we also discuss a pattern-recognition system which works with the mechanism of the neocognitron. The system has been implemented on a minicomputer and ha...
متن کاملAn Evaluation of Mahalanobis-Taguchi System and Neural Network for Multivariate Pattern Recognition
The Mahalanobis-Taguchi System is a diagnosis and predictive method for analyzing patterns in multivariate cases. The goal of this study is to compare the ability of the Mahalanobis- Taguchi System and a neural-network to discriminate using small data sets. We examine the discriminant ability as a function of data set size using an application area where reliable data is publicly available. The...
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: IEEE Transactions on Neural Networks
سال: 2007
ISSN: 1045-9227
DOI: 10.1109/tnn.2006.884677