Sufficient Conditions for One-Dimensional Cellular Neural Networks to Perform Connected Component Detection
نویسندگان
چکیده
It is well known that one-dimensional cellular neural networks (1-D CNNs) with the template A = [1, 2,−1] can perform connected component detection (CCD). However this has been confirmed only by numerical and laboratory experiments. In this paper, sufficient conditions for 1-D CNNs to perform CCD are obtained through theoretical analysis. Main result shows that a wide class of templates including A = [1, 2,−1] can be used for CCD.
منابع مشابه
Linear matrix inequality approach for synchronization of chaotic fuzzy cellular neural networks with discrete and unbounded distributed delays based on sampled-data control
In this paper, linear matrix inequality (LMI) approach for synchronization of chaotic fuzzy cellular neural networks (FCNNs) with discrete and unbounded distributed delays based on sampled-data controlis investigated. Lyapunov-Krasovskii functional combining with the input delay approach as well as the free-weighting matrix approach are employed to derive several sufficient criteria in terms of...
متن کاملFault Detection and Location in DC Microgrids by Recurrent Neural Networks and Decision Tree Classifier
Microgrids have played an important role in distribution networks during recent years. DC microgrids are very popular among researchers because of their benefits. Protection is one of the significant challenges in the way of microgrids progress. As a result, in this paper, a fault detection and location scheme for DC microgrids is proposed. Due to advances in Artificial Intelligence (AI) and s...
متن کاملA Two-Dimensional Convolutional Neural Network for Brain Tumor Detection From MRI
Aims: Cancerous brain tumors are among the most dangerous diseases that lower the quality of life of people for many years. Their detection in the early stages paves the way for the proper treatment. The present study aimed to present a two-dimensional Convolutional Neural Network (CNN) for detecting brain tumors under Magnetic Resonance Imaging (MRI) using the deep learning method. Methods & ...
متن کاملJoint influence of leakage delays and proportional delays on almost periodic solutions for FCNNs
This paper deals with fuzzy cellular neural networks (FCNNs) with leakage delays and proportional delays. Applying the differential inequality strategy, fixed point theorem and almost periodic function principle, some sufficient criteria which ensure the existence and global attractivity of a unique almost periodic solution for fuzzy cellular neuralnetworks with leakage delays and p...
متن کاملDetermining Effective Features for Face Detection Using a Hybrid Feature Approach
Detecting faces in cluttered backgrounds and real world has remained as an unsolved problem yet. In this paper, by using composition of some kind of independent features and one of the most common appearance based approaches, and multilayered perceptron (MLP) neural networks, not only some questions have been answered, but also the designed system achieved better performance rather than the pre...
متن کامل