同步动态循环神经网络模型中的对称序列处理
Symmetric sequence processing in a recurrent neural network model with a synchronous dynamics
摘要：
在这项工作中，允许存在一个自我相互作用的对称序列处理和Hebbian模式重建之间的竞争突触的循环吸引子神经网络模型的同步动力学和稳态进行了研究。在没有噪声的情况下，得到了定态的相图，表现出恢复、对称和周期两个循环态以及相关和冻结态的相位。冻结状态不稳定的突触噪声和分离区域的相关和循环状态。兴奋性或抑制性自我相互作用产生固定点或循环行为的扩大阶段。
英文摘要：
The synchronous dynamics and the stationary states of a recurrent attractor neural network model with competing synapses between symmetric sequence processing and Hebbian pattern reconstruction is studied in this work allowing for the presence of a self-interaction for each unit. Phase diagrams of stationary states are obtained exhibiting phases of retrieval, symmetric and period-two cyclic states as well as correlated and frozen-in states, in the absence of noise. The frozen-in states are destabilised by synaptic noise and well separated regions of correlated and cyclic states are obtained. Excitatory or inhibitory self-interactions yield enlarged phases of fixed-point or cyclic behaviour.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
