Neural processor in artificial intelligence advancement
Journal: Journal of Autonomous Intelligence DOI: 10.32629/jai.v1i1.13
Abstract
A neuron network is a computational model based on structure and functions of biological neural networks. Information that flows through the network affects the structure of the neuron network because neural network changes-or learns, in a sense-based on that input and output. Although neural network being highly complex (for example change of weights for every new data within the time frame) an experimental model of high level architecture of neural processor is proposed. Neural Processor performs all the functions that an ordinary neural network does like adaptive learning, self-organization, real time operations and fault tolerance. In this paper, analysis of neural processing is discussed and presented with experiments, graphical representation including data analysis.
Keywords
Neuron; neuron processor; neuron network; artificial intelligence
Full Text
PDF - Viewed/Downloaded: 45 TimesIndexation
Download Index RecordReferences
1. Shbier M. Introduction to artificial neuron networks. Available from: https://tmohammed. files.wordpress.com/2012/03/w1-01-introtonn. ppt.
2. Woodford C. Introduction to neural networks. Available from: http://www.explainthatstuff. com/introduction-to-neural-networks.html.
3. Introduction to deep neural networks. Available from: https://deeplearning4j.org/neuralnet-overview.
4. Processor Architecture Patterns. Available from: http://w ww.eventhelix.com/RealtimeMantra/Patterns/processor_ architecture_patterns.htm#.Wa7v8rJ97Dd.
5. Artificial neural networks technology. Available from: http://irrigation.rid.go.th/rid15/ppn/Knowledge/Artificial%20 Neuron%20Networks%20Technology/4.0%20 Neural%20Networks%20Components.htm
6. Block Diagram Image Credit. Available from: http://research.library.mun.ca/9042/1/Balasubramanian_Balamurugan.pdf.
7. Coss J. Neural chase. Available from: https://sourceforge.net/projects/neuralchase/.
8. Simbrain simulator for neuron processing. Available from: http://simbrain.net/index.html.
9. Danese G, Leporati F, Ramat S. A parallel neural processor for real-time applications. Available from: http://brahms.di.uminho.pt/discip/MInf/ac0203/ICCA03/ParallNeuProc. pdf.
10. Tensor flow for neurons. Available from: http://playground.tensorflow.org.
2. Woodford C. Introduction to neural networks. Available from: http://www.explainthatstuff. com/introduction-to-neural-networks.html.
3. Introduction to deep neural networks. Available from: https://deeplearning4j.org/neuralnet-overview.
4. Processor Architecture Patterns. Available from: http://w ww.eventhelix.com/RealtimeMantra/Patterns/processor_ architecture_patterns.htm#.Wa7v8rJ97Dd.
5. Artificial neural networks technology. Available from: http://irrigation.rid.go.th/rid15/ppn/Knowledge/Artificial%20 Neuron%20Networks%20Technology/4.0%20 Neural%20Networks%20Components.htm
6. Block Diagram Image Credit. Available from: http://research.library.mun.ca/9042/1/Balasubramanian_Balamurugan.pdf.
7. Coss J. Neural chase. Available from: https://sourceforge.net/projects/neuralchase/.
8. Simbrain simulator for neuron processing. Available from: http://simbrain.net/index.html.
9. Danese G, Leporati F, Ramat S. A parallel neural processor for real-time applications. Available from: http://brahms.di.uminho.pt/discip/MInf/ac0203/ICCA03/ParallNeuProc. pdf.
10. Tensor flow for neurons. Available from: http://playground.tensorflow.org.
Copyright © 2018 Manu Mitra
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License