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Global Stabilization of Memristive Neural Networks with Leakage and Time-Varying Delays Via Quantized Sliding-Mode Controller

机译:通过量化滑模控制器的泄漏和时变延迟的全局稳定性难题

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This pape investigates the global stabilization of memristive neural networks (MNNs) with leakage and time-varying delays via quantized sliding-mode controller. The leakage delay is considered in the MNNs. Sliding mode controller is imported to ensure global stabilization of delayed MNNs. We also introduce two quantization schemes with uniform quantizer and logarithmic quantizer. Our goal is to deal with errors before and after quantization. We give some simulations and comparisons between two quantizers in the end of this paper.
机译:该PAPE通过量化的滑模控制器调查具有泄漏和时变延迟的忆阻神经网络(MNN)的全球稳定。在MNN中考虑泄漏延迟。导入滑模控制器以确保延迟MNN的全局稳定。我们还使用统一的量化器和对数量化器引入了两个量化方案。我们的目标是在量化之前和之后处理错误。我们在本文末尾提供了两种量化器之间的一些模拟和比较。

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