Acoustic emission-based techniques are promising for nondestructive inspection of mechanical systems. For reliable automatic fault monitoring, it is important to identify the transient crack-related signals in the presence of strong timevarying noise and other interference. In this paper we propose the application of the Kohonen network for this purpose. The principal components of the short-ti...

A system based on a neural network framework is considered. We used two neural networks, an Elman network [1][2] and a Kohonen (concurrent) network [3], for a categorization task. The input of the system are objects derived from three general prototypes: circle, square, polygon. We varied the size and orientation of the objects in a continuous way. The system is trained using a new algorithm, b...

Priyanka Khandelwal , Krishna Kant Singh , B.K.Singh , Akansha Mehrotra 1 Electronics & Communication Engineering, BTKIT, Dwarhat, India 2 Earthquake Engineering, IIT, Roorkee, India 1 [email protected] [email protected] 2 [email protected] [email protected] Abstract— In this paper, an unsupervised change detection technique of multispectral images based on wavelet fusion ...

The traditional approaches of classification are always unfavorable in the description of information distribution. This paper describes the BP neural network approach and the Kohonen neural network approach to the classification of remote sensing images. Two algorithms have their own traits and can be good used in the classification. A qualitative comparison demonstrates that both original ima...

We present a Self-Organizing Kohonen Neural Network for quantizing colour graphics images. The network is compared with existing algorithmic methods for colour quantization. It is shown experimentally that, by adjusting a quality factor, the network can produce images of much greater quality with longer running times, or slightly better quality with shorter running times than the existing metho...

An initialization mechanism is presented for Kohonen neural network implemented in CMOS technology. Proper selection of initial values of neurons’ weights has a large influence on speed of the learning algorithm and finally on the quantization error of the network, which for different initial parameters can vary even by several orders of magnitude. Experiments with the software model of designe...

Recent developments of Self-Organizing Maps or Kohonen networks become more and more interesting in many fields such as: pattern recognition, clustering, speech recognition, data compression, medical diagnosis... Kohonen networks is unsupervised learning models. The results obtained by the Kohonen networks are dependent on their parameters such as the architecture of the Kohonen map, the later ...