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该论文提出 HRF-Res，一种用谐振放电（HRF）神经元替代传统 LIF 神经元的液态状态机，使脉冲储层具备频率选择性动力学，在十个基准上达到脉冲储层方法的最先进精度，同时比等效非脉冲振荡储层能耗降低多达 19 倍。
SHARP introduces a bio-inspired framework that separates memory accumulation from pattern recognition, using accelerated replay during offline sleep phases to learn long-range non-stationary temporal patterns in streaming settings. It improves context retention on text8 and PG-19 while maintaining computational efficiency.