网络结构 Resources

Showing items tagged with "网络结构"

This resource implements the LeNet-5 architecture for the MNIST dataset, adapting the original network structure by modifying input dimensions to 28×28 pixels. The implementation draws inspiration from UFLDL tutorials and R. B. Palm's CNN codebase. Key modifications include full connectivity between C3 and S4 feature maps, achieving 99.1% accuracy through optimized training procedures with data augmentation and regularization techniques.

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The unit shortest path algorithm using maximum adjacency point storage utilizes the maximum number of adjacent nodes in a network as a key parameter. By taking the maximum adjacency count as matrix columns and total node count as rows, it constructs an adjacency node matrix M-PJ to describe network topology. Rows are ordered by ascending node indices, with adjacent nodes of node I listed in row I. If a node has fewer adjacent nodes than the maximum, zeros pad the remaining positions. Corresponding edge weights are mapped to create an initial judgment matrix M-PDJ. Using these matrices, the algorithm efficiently computes shortest paths between any two nodes while optimizing storage through fixed-size matrix structures.

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IEEE various node diagrams for reference only. In power system analysis and computation, different network structures and parameters are required. Before applying these parameters, data collection and organization can be time-consuming.

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