A Novel Liapunov Function for Additive Neural Networks
Using the properties of nonlinear integral equations of the Hammerstein type, it is proven that a new Liapunov function for additive neural networks exists, provided two conditions on symmetry and positivity of the weight matrix hold. The function does not require monotonicity of the transfer function.
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