Improved Back Propagation Algorithm to Avoid Local Minima in Multiplicative Neuron Model
作者： Kavita Burse , Manish Manoria , Vishnu Pratap Singh Kirar
DOI: 10.1007/978-3-642-20573-6_11
关键词: Backpropagation 、 Algorithm 、 Artificial neural network 、 Maxima and minima 、 Multiplicative function 、 Computer science 、 Back propagation algorithm 、 Term (time) 、 Artificial intelligence
摘要: The back propagation algorithm calculates the weight changes of artificial neural networks, and a common approach is to use training consisting learning rate momentum factor. major drawbacks above are problems local minima slow convergence speeds. addition an extra term, called proportional factor reduces algorithm. We have applied three term multiplicative network learning. tested on XOR parity problem compared with standard
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