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Application of Multi Layer (Perceptron) Artificial Neural Network in the Diagnosis System: A Systematic Review
Proceedings of the 2018 3rd IEEE International Conference on Research in Intelligent and Computing in Engineering, RICE 2018 Số , năm 2018 (Tập , trang -)
ISSN: 141593
ISSN: 141593
DOI: 10.1109/RICE.2018.8509069
Tài liệu thuộc danh mục: Scopus
Proc. IEEE Int. Conf. Res. Intell. Comput. Eng., RICE
English
Từ khóa: Backpropagation algorithms; Computer hardware; Computer hardware description languages; Diagnosis; Engineering research; Field programmable gate arrays (FPGA); Hardware; Intelligent computing; Neural networks; Neurons; Reconfigurable architectures; Backpropagation learning algorithm; Diagnosis systems; Input neurons; Multi layer perceptron; Reconfigurable computing systems; Research papers; Systematic Review; Multilayer neural networks
Tóm tắt tiếng anh
Basic hardware comprehension of an artificial neural network (ANN), to a major scale depends on the proficient realization of a distinct neuron. For hardware execution of NNs, mostly FPGA-designed reconfigurable computing systems are favorable. FPGA comprehension of ANNs through a huge amount of neurons is mainly an exigent assignment. This work converses the reviews on various research articles of neural networks whose concerns focused in execution of more than one input neuron and multilayer with or without linearity property by using FPGA. An execution technique through reserve substitution is projected to adjust signed decimal facts. A detailed review of many research papers have been done for the proposed work. The proposed paper involves a Multi Layer Perceptron with a Back Propagation learning algorithm to identify a prototype for the diagnosis. In this paper, a brief introduction about artificial neural network used nowadays for diagnosis of disease is given. � 2018 IEEE.
