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Application of Multi Layer Artificial Neural Network in the Diagnosis System: A Systematic Review

机译:多层人工神经网络在诊断系统中的应用:系统综述

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Basic hardware comprehension of an artificial neural network (ANN), to a major scale depends on the proficientrealization of a distinctneuron. For hardware execution of NNs, mostly FPGA-designed reconfigurable computing systems are favorable .FPGA comprehension of ANNs through a hugeamount of neurons is mainlyan exigentassignment. This workconverses the reviews on various research articles of neural networks whose concernsfocused in execution of more than one input neuron and multilayer with or without linearity property by using FPGA. An execution technique through reserve substitution isprojected to adjust signed decimal facts. A detailed review of many research papers have been done for the proposed work.
机译:人工神经网络(ANN)的基本硬件理解在很大程度上依赖于独特神经元的熟练实现。对于神经网络的硬件执行,大多数都是由FPGA设计的可重构计算系统是有利的。通过大量的神经元对神经网络的FPGA理解主要是一个实例。这项工作与有关神经网络的各种研究文章的评论相反,这些研究关注的焦点是通过使用FPGA执行多个输入神经元和具有或不具有线性特性的多层神经元。通过储备替代的执行技术预计将调整带符号的十进制事实。对于建议的工作,已经完成了许多研究论文的详细审查。

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