Artificial Neural Network
Artificial Neural Network Sphoorti Sood1and Divya Gupta2 1{Student of Computer Science Department SRMSWCET, Bareilly} sphoortisood@yahoo.in 2{Student of Computer Science Department SRMSWCET, Bareilly} divyagupta1309@gmail.com Abstract— Artificial neural networks (ANNs) are simplified models of human brain. These are networks of computing elements that have the ability to respond to input stimuli and generate the corresponding output. To obtain a desirable output, the network weights must be trained upon the available data many times. Hence the software realization of ANN takes many hours to learn a particular example .This paper include the several advancement of ANN in cluster which would help us in the study of data mining, data compression, exploratory analysis or other aspect related to cluster. The cluster help ,us in the pattern matching that explore the cluster algorithm and place the similar pattern in the cluster. It highlights the important issues related and shows the possible direction of future research.
Keywords- Artificial neural network, Data clustering ,data compression, data mining ,exploratory analysis, pattern matching.
I. INTRODUCTION
The modern usage of the term neural network is refers to artificial neural networks, which are composed of artificial neurons or nodes Artificial neural networks are composed of interconnecting artificial neurons. These neurons are connected through a network structure. Once a network has been structured for a particular application, that network is ready to be trained. We know that there are several learning methods for the training to that network like: Supervised Learning, Unsupervised Learning, Reinforced Learning etc.
Through this approach we can train the computing data that are represented in a structure or network, often tabular , a tree or a graph structure. Clustering is used to
Keywords- Artificial neural network, Data clustering ,data compression, data mining ,exploratory analysis, pattern matching.
I. INTRODUCTION
The modern usage of the term neural network is refers to artificial neural networks, which are composed of artificial neurons or nodes Artificial neural networks are composed of interconnecting artificial neurons. These neurons are connected through a network structure. Once a network has been structured for a particular application, that network is ready to be trained. We know that there are several learning methods for the training to that network like: Supervised Learning, Unsupervised Learning, Reinforced Learning etc.
Through this approach we can train the computing data that are represented in a structure or network, often tabular , a tree or a graph structure. Clustering is used to
References: [5] M.J. Zurada, "Introduction to Artificial Neural System Jacbio Publishing Mouse”, New Delhi(1999).