The Bifurcating Neuron Network 2: an analog associative memory
The Bifurcating Neuron Network 2: an analog associative memory
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分叉神经元网络 2：模拟联想记忆
DOI：
10.1016/s0893-6080(01)00100-9
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发表时间：
2002
期刊：
影响因子：
--
通讯作者：
N. Farhat
中科院分区：
文献类型：
--
作者：
Geehyuk Lee;N. Farhat
分叉神经元（BN）是一种混沌积分激发神经元，是一种通过来自环境的相干调制增强的神经元模型。BN在数学上等价于正弦圆映射，这种等价关系使我们能够将一维映射的数学应用于BN网络的设计。对BN分叉图的研究表明，在适当的条件下，BN可以起到幅相转换器的作用。此外，作为一个集成和发射神经元，它具有作为重合检测器的固有能力。这两个观察结果使我们设计了BN网络2（BNN-2），这是一种脉冲耦合神经网络，具有多个模拟模式的联想记忆。除了作为联想记忆的常见动力学特性外，BNN-2还表现出体积全息记忆：随着相干调制频率的变化，它会切换到其记忆空间的不同页面，这意味着上下文敏感的记忆。
The Bifurcating Neuron (BN), a chaotic integrate-and-fire neuron, is a model of a neuron augmented by coherent modulation from its environment. The BN is mathematically equivalent to the sine-circle map, and this equivalence relationship allowed us to apply the mathematics of one-dimensional maps to the design of a BN network. The study of the bifurcating diagram of the BN revealed that the BN, under a suitable condition, can function as an amplitude-to-phase converter. Also, being an integrate-and-fire neuron, it has an inherent capability to function as a coincidence detector. These two observations led us to the design of the BN Network 2 (BNN-2), a pulse-coupled neural network that exhibits associative memory of multiple analog patterns. In addition to the usual dynamical properties as an associative memory, the BNN-2 was shown to exhibit volume-holographic memory: it switches to different pages of its memory space as the frequency of the coherent modulation changes, meaning context-sensitive memory.
DOI：
10.1016/0013-4694(80)90319-3
发表时间：
1980-01-01
期刊：
ELECTROENCEPHALOGRAPHY AND CLINICAL NEUROPHYSIOLOGY
影响因子：
--
作者：
BRESSLER, SL;FREEMAN, WJ
通讯作者：
FREEMAN, WJ