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Physical grounds and models of pattern representation and recognition in a neuron cytoskeleton microtubule

机译:神经元细胞骨架微管中模式表示和识别的物理基础和模型

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The physics of the dipole system of a neuron cytoskeleton microtubule is put forward, and a Hamiltonian of the dipole system is constructed. The previously developed microscopic model of the cytoskeleton microtubule dipole system is extended for the case of dipole-dipole bonds when the bonds are not fully ordered and are constrained (exhibit the memory property). Molecular field expressions are derived for a random polarization function and its two moments: mean polarization and rms polarization. An evolutionary equation for a random order parameter is of a relaxation character and describes the pattern recognition process. It is shown that the phase transition nonlinearly transforms (projects) one (nodal) space of higher dimension pattern features to another space of lower dimension attributes (order parameters), this transformation greatly cutting the body of data to be processed.
机译:提出了神经元细胞骨架微管的偶极子系统的物理学,并构建了偶极子系统的哈密顿量。当偶极-偶极键的结合不完全有序且受约束(表现出记忆特性)时,先前开发的细胞骨架微管偶极系统的微观模型得以扩展。推导了随机极化函数及其两个矩的分子场表达式:平均极化和均方根极化。随机顺序参数的演化方程具有松弛特性,描述了模式识别过程。结果表明,相变将高维图案特征的一个(节点)空间非线性转换(投影)为低维属性(顺序参数)的另一空间,这种转换极大地削减了要处理的数据主体。

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