方法证据记录
Echo State Network
An Echo State Network (ESN) is a type of recurrent neural network introduced by Herbert Jaeger and Harald Haas in 2004 that exploits a large, randomly connected, fixed recurrent layer — the reservoir — to project input signals into a high-dimensional nonlinear space. Only the linear output weights are trained, typically via ridge regression, making ESNs computationally inexpensive yet highly expressive for temporal and chaotic time-series modeling tasks.
源记录
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Echo State Network (Reservoir Computing)
分类方法记录 · ml-model / deep-learning
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