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Analytic expressions for the BCDMEM model of recognition memory

机译:识别记忆的BCDMEM模型的解析表达式

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We introduce a Fourier transformation technique that enables one to derive closed-form expressions of performance measures (e.g., hit and false alarm rates) of simulation-based models of recognition memory. Application of the technique is demonstrated using the bind cue decide model of episodic memory (BCDMEM; [Dennis, S., & Humphreys, M.S. (2001). A context noise model of episodic word recognition. Psychological Review, 108(2), 452-4781). In addition to reducing the time required to test the model, which for models like BCDMEM can be excessive, asymptotic expressions of the measures reveal heretofore unknown properties of the model, such as model predictions being dependent on vector length. (c) 2007 Elsevier Inc. All rights reserved.
机译:我们介绍了一种傅立叶变换技术,该技术可使人得出基于模拟的识别记忆模型的性能指标(例如命中率和误报率)的闭式表达式。使用情景记忆的绑定提示决定模型(BCDMEM; [Dennis,S.&Humphreys,MS(2001)。情景词识别的上下文噪声模型。),《心理评论》,108(2),452证明了该技术的应用。 -4781)。除了减少测试模型所需的时间(对于像BCDMEM这样的模型而言,这可能是多余的)之外,这些措施的渐进表达式还揭示了该模型迄今未知的属性,例如,模型预测取决于矢量长度。 (c)2007 Elsevier Inc.保留所有权利。

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