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[matlabElman

Description: MATLAB程序编写的神经网络ELMAN算法,实现故障模式识别-MATLAB programming Elman neural network algorithm, the fault pattern recognition
Platform: | Size: 1024 | Author: michael | Hits:

[Special EffectsMATLAB_optical_flow

Description: The code implements the optical flow algorithm described in Gautama, T. and Van Hulle, M.M. (2002). A Phase-based Approach to the Estimation of the Optical Flow Field Using Spatial Filtering,IEEE Trans. Neural Networks, 13(5), 1127--1136. The algo proceeds in 3 steps 1. spatial filtering 2. phase gradient estimation 3. IOC using recurrent networks -The code implements the optical flow algor ithm described in Gautama, and T. Van Hulle. M.M. (2002). A Phase-based Approach to the Esti mation of the Optical Flow Field Using Spatial F iltering, IEEE Trans. Neural Networks, 13 (5), 1127-- 1136. The algo proceeds in a three steps. spat ial filtering 2. 3 phase gradient estimation. I OC using recurrent networks
Platform: | Size: 658432 | Author: Jallon | Hits:

[AI-NN-PRESNtools

Description: 回声状态神经网络(ESN)是一种性能优异的递归神经网络,已经在各领域广泛研究,这是ESN的发明人研制的MATLAB工具箱,可供有关人员参考使用-Echo state neural networks (ESN) is a performance of recurrent neural networks have been extensively studied in various fields, which is ESN inventor developed MATLAB toolbox, use and reference available to the persons
Platform: | Size: 101376 | Author: xu mark | Hits:

[Data structsERN

Description: a transmission line fault location model which is based on an Elman recurrent network (ERN) has been presented for balanced and unbalanced short circuit faults. All fault situations with different inception times are implemented on a 380-kV prototype power system. Wavelet transform (WT) is used for selecting distinctive features about the faulty signals. The system has the advantages of utilizing single-end measurements, using both voltage and current signals. ERN is able to determine the fault location occurred on transmission line rapidly and correctly as an important alternative to standard feedforward back propagation networks (FFNs) and radial basis functions (RBFs) neural networks.
Platform: | Size: 761856 | Author: charlie | Hits:

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