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拿verilog编写的som(自适应神经网络算法)，用于障碍物检测，基于FPGA可综合实验，已经在altera的cylcone上实现-Canal verilog prepared som (adaptive neural network algorithm) for obstacle detection. Based on FPGA synthesis experiments, in altera achieve the cylcone
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本文为通信专业硕士研究生的毕业论文。主要研究神经网络的FPGA实现及其在网络拥塞控制中的应用。
-In this paper, for the communications professional Master s thesis. Major study of the FPGA realization of neural networks and its application in network congestion control applications.
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用Handel-c语言编写的，神经网络在fpga中的实现-With the Handel-c language, the neural network implementation in fpga
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神经网络的FPGA实现参考，ANN的实时硬件计算越来越受到重视。-Neural network FPGA implementation reference, ANN real-time hardware computing draws more and more attention.
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BP神经网络的前向计算硬件程序，经过FPGA调试。-BP neural network hardware prior to the calculation procedure, through the FPGA debug.
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基于FPGA的神经网络硬件实现方法损失是否-Neural network hardware implementation based on FPGA
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基于fpga的自适应神经网络算法-Fpga-based adaptive neural network algorithm
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Neural Network with FPGA and VHDL codes + Matlab model
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自适应神经网络算法，用于障碍物检测，基于FPGA可综合实验-Adaptive neural network algorithm for obstacle detection, based on the FPGA can be integrated experiment
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在PYNQ-Z1上搭建二值神经网络(BNN)(Building two value neural network (BNN) on PYNQ-Z1)
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Convolutional neural network code for fpga
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