Inversion in Time

Inversionof multilayersynchronous networks is a method which tries to answer questions like What kind of input will give a desired output?" or Is it possible to get a desired output under special input output constraints?". We will describe two methods of inverting a connectionist network. Firstly, we extend inversion via backpropagation Linden Kindermann 4 , Williams 11 to recurrent Elman 1 , Jordan 3 , Mozer 5 , Williams Zipser 10 , time-delayed Waibel at al. 9 and discrete versions of continuous networks Pineda 7 , Pearlmutter 6 . The result of inversion is an input vector. The corresponding output vector is equal to the target vector except a small remainder. The knowledge of those attractors may help to understand the function and the generalization qualities of connectionist systems of this kind. Secondly, we introduce a new inversion method for proving the non-existence of an input combination under special constraints, e.g. in a subspace of the input space. This met...

• Type: Conference
• Year: 1990
• Where: EURASIP
• Authors: Sebastian Thrun, Alexander Linden
• Keywords: Corresponding Output Vector, EURASIP 1990, Input, Input Output Constraints, Neural Networks