Analysis of Artificial Neural-Network IJTSRD
An Artificial Neural Network ANN is a computational model that is inspired by the way biological neural networks in the human brain process information. Artificial Neural Networks have generated a lot of excitement in Machine Learning research and industry, thanks to many breakthrough results in speech recognition, computer vision and text processing. In this blog post we will try to develop an understanding of a particular type of Artificial Neural Network called the Multi Layer Perceptron. An Artificial Neural Network ANN is an information processing paradigm that is inspired by the way biological nervous systems, such as the brain, process information. The key element of this paradigm is the novel structure of the information processing system. It is composed of a large number of highly interconnected processing elements neurons working in unison to solve specific problems. ANNs, like people, learn by example. An ANN is configured for a specific application, such as pattern recognition or data classification, through a learning process. Learning in biological systems involves adjustments to the synaptic connections that exist between the neurones. This is true for ANNs as well.
Rajesh CVS | Nadikoppula Pardhasaradhi “Analysis of Artificial Neural-Network”
Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-2 | Issue-6 , October 2018,
Analysis of Artificial Neural-Network IJTSRD IEEE PAPER
Multimodal Biometrics Authentication System using Fusion of Fingerprint and Iris IJTSRD
Voltage Regulation in Grid Connected Power System Using 24 Pulse STATCOM IJTSRD