Parameterization of connectionist models
Parameterization of connectionist models
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DOI：
10.3758/bf03206554
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发表时间：
2004-11-01
期刊：
影响因子：
--
通讯作者：
Cohen, JD
中科院分区：
文献类型：
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作者：
Bogacz, R;Cohen, JD
我们提出了一种估计连接主义模型参数的方法，该方法允许模型的输出尽可能接近经验数据。该方法最小化成本函数，该函数测量从模型输出计算的统计数据与从受试者性能计算的统计数据之间的差异。优化算法找到使该代价函数的值最小的参数值。成本函数还表明模型的统计数据是否与数据的统计数据有显著差异。在某些情况下，该方法可以自动找到最优参数。在其他情况下，该方法可以方便人工搜索最优参数。该方法已经在Matlab中实现，有完整的文档，并且可以从心理学会Web档案（www.psychonomic.org/archive/）免费下载。
We present a method for estimating parameters of connectionist models that allows the model's output to fit as closely as possible to empirical data. The method minimizes a cost function that measures the difference between statistics computed from the model's output and statistics computed from the subjects' performance. An optimization algorithm finds the values of the parameters that minimize the value of this cost function. The cost function also indicates whether the model's statistics are significantly different from the data's. In some cases, the method can find the optimal parameters automatically. In others, the method may facilitate the manual search for optimal parameters. The method has been implemented in Matlab, is fully documented, and is available for free download from the Psychonomic Society Web archive at www.psychonomic.org/archive/.