Description: 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 Platform: |
Size: 5857 |
Author:刘索山 |
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Description: 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 Platform: |
Size: 5120 |
Author:刘索山 |
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Description: 显卡中关于3D图形处理的源码，是VHDL版本的
喜欢硬件FPGA图像处理的可以看看，挺有意思-Graphics 3D graphics on the source, is like VHDL version of the FPGA hardware image processing can see quite interesting Platform: |
Size: 1686528 |
Author:dido wang |
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Description: 提出了利用FPGA的现场可编程以及可并行处理的特性，对基于人工神经网络的图像处理结构进行自动生成的一种技术。作者：Andre B. Soares, Altamiro A. Susin，Leticia V. Guimaraes-Made use of field-programmable FPGA, as well as the characteristics of parallel processing, artificial neural network-based image processing to automatically generate the structure of a technology. Author: Andre B. Soares, Altamiro A. Susin, Leticia V. Guimaraes Platform: |
Size: 1055744 |
Author:Rae |
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Description: 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. Platform: |
Size: 1291264 |
Author:张三 |
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Description: 神经网络算法的FPGA实现，英文版，具有很强的实用价值-Neural network algorithm to achieve the FPGA, in English, has a strong practical value Platform: |
Size: 3942400 |
Author:HENRRY |
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Description: Based on the information processing functionalities of spiking neurons, a spiking neural network model is proposed to extract features from a visual image. The network is constructed with a conductance-based integrate-and-fire neuron model and a set of specific receptive fields. The properties of the network are detailed in this paper. Simulation results show that the network is able to perform image feature extraction within a time interval of 100 ms. This processing time is consistent with the human visual system. The demonstrations show how the network can extract right-angle contours in a visual image. Based on this principle, many other image features can be extracted by analogy. The parallel processing mechanism of this network model is very promising for a hardware implementation based on VLSI or FPGA technology. Platform: |
Size: 288768 |
Author:sacoura31 |
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Description: 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. Platform: |
Size: 3889152 |
Author:minigiss2 |
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Search - Neural Network FPGA