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An iterative calculation method of neuron model with sigmoid function

机译:乙状结肠神经元模型的迭代计算方法

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摘要

Neural network hardware is necessary for demanding real-time applications such as pattern recognition. In the paper, an improved calculation algorithm of the neuron model with sigmoid function is proposed, which is suitable for hardware implementation. The algorithm is based on the multi dimensional binary search. The neuron circuits implemented on FPGA by the proposed algorithm have shown excellence in size and circuit frequency compared with the conventional circuits with sum of product operation.
机译:对于诸如模式识别之类的实时应用而言,神经网络硬件是必不可少的。提出了一种改进的具有S形函数的神经元模型计算算法,该算法适合于硬件实现。该算法基于多维二进制搜索。与传统的电路相比,通过所提出的算法在FPGA上实现的神经元电路在大小和电路频率上表现优异,并且具有乘积运算的总和。

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