Fusion: Practice and Applications FPA 2692-4048 2770-0070 10.54216/FPA https://www.americaspg.com/journals/show/822 2018 2018 A Hybrid Approach for Neural Network in Pattern Storage Department of Computer Science and Engineering, Chandigarh University, Gharuan, Punjab, 140413, India Kumud Sachdeva Department of Computer Science and Engineering, Chandigarh University, Gharuan, Punjab, 140413, India Shruti Aggarwal Your mind does not manufacture your mind. Your mind forms neural networks. Neural networks had been effectively carried out to numerous sample garage and type troubles in phrases in their mastering ability, excessive discrimination electricity, and exceptional generalization ability. The achievement of many mastering schemes isn't always assured, however, seeing that algorithms like backpropagation have many drawbacks like stepping into the nearby minima, for that reason imparting suboptimal solutions. In the case of classifying big sets and complicated patterns, the traditional neural networks are afflicted by numerous problems inclusive of the dedication of the shape and length of the network, the computational complexity, and so on. This paper introduces neural computing techniques especially radial foundation features network. Various upgrades and trends made in an artificial neural network for rushing up training, keeping off nighborhood minima, growing the generalization capacity and different capabilities are reviewed. 2021 2021 43 49 10.54216/FPA.060201 https://www.americaspg.com/articleinfo/3/show/822