In this paper, we extend an available neural network verification technique to support a wider class of piece-wise linear activation functions. Furthermore, we extend the algorithms, which provide in their original form exact respectively over-approximative results for bounded input sets represented as start sets, to allow also unbounded input set. We implemented our algorithms and demonstrated their effectiveness in some case studies.

翻译：本文扩展了一种现有的神经网络验证技术，以支持更广泛的逐段线性激活函数类别。此外，我们将原有算法（其原始形式可针对表示为起始集的有界输入集提供精确或过逼近结果）进行扩展，使其同样能够处理无界输入集。我们实现了所提出的算法，并通过若干案例研究验证了其有效性。