Method of computing gradient vector and Jacobean matrix in arbitrarily connected neural networks

@article{Wilamowski2007MethodOC,
  title={Method of computing gradient vector and Jacobean matrix in arbitrarily connected neural networks},
  author={B. M. Wilamowski and N. Cotton and Okyay Kaynak and G. Dundar},
  journal={2007 IEEE International Symposium on Industrial Electronics},
  year={2007},
  pages={3298-3303}
}
The paper shows that it fully connected neural networks are used then the same problem can be solved with less number of neurons and weights. Interestingly such networks are trained faster. The problem is that most of the neural networks terming algorithms are not suitable for such network. Presented algorithm and software allow training feedforwad neural networks with arbitrarily connected neurons in similar way as the SPICE program can analyze any circuit topology. When the second order… CONTINUE READING