论文标题
手稿符号的熵关联记忆
Entropic Associative Memory for Manuscript Symbols
论文作者
论文摘要
手稿符号可以从熵和分布但尚未声明的熵数字记忆中存储，识别和检索；内存检索是一种建设性操作，在没有搜索的情况下直接拒绝内存中未包含的对象的内存提示，并且可以通过并行计算执行内存操作。手稿符号（字母和数字）在具有关联的熵的关联内存寄存器中表示。内存识别操作遵守精度和召回之间的熵权衡，熵水平会影响通过内存检索操作恢复的对象的质量。本建议在几个维度与关联记忆的神经网络模型形成对比。我们讨论了熵关联记忆的操作特征，以检索具有完整和不完整信息的对象，例如严重的遮挡。本文报告的实验增加了有关该框架开发实际应用和自然记忆计算模型的潜力的证据。
Manuscript symbols can be stored, recognized and retrieved from an entropic digital memory that is associative and distributed but yet declarative; memory retrieval is a constructive operation, memory cues to objects not contained in the memory are rejected directly without search, and memory operations can be performed through parallel computations. Manuscript symbols, both letters and numerals, are represented in Associative Memory Registers that have an associated entropy. The memory recognition operation obeys an entropy trade-off between precision and recall, and the entropy level impacts on the quality of the objects recovered through the memory retrieval operation. The present proposal is contrasted in several dimensions with neural networks models of associative memory. We discuss the operational characteristics of the entropic associative memory for retrieving objects with both complete and incomplete information, such as severe occlusions. The experiments reported in this paper add evidence on the potential of this framework for developing practical applications and computational models of natural memory.
