Paper Computers, Imaginary Values and the Emergence of Fermions

Louis H. Kauffman

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Paper Computers, Imaginary Values and the Emergence of Fermions

机译：纸计算机，虚构价值和费米子的出现

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This paper shows how, when Boolean algebra turns upon itself and becomes self-referential, the elements of oscillation, memory, counting, imaginary values and the beginnings of quantum physics in the form of Fermions and the Dirac equation are born. laws of form; marked state; unmarked state; self reference; Boolean algebra; Boolean arithmetic; circuit; memory; oscillator; modulator; time; synchronous; asynchronous; imaginary value; iterant; iterant algebra; Clifford algebra; Fermion algebra; relativity; Dirac equation.

机译：本文说明了当布尔代数重新出现并成为自指代时，振荡，记忆，计数，虚数值以及费米子和狄拉克方程形式的量子物理学的起源是如何诞生的。形式定律;标记状态未标记状态；自我参考；布尔代数布尔运算；电路记忆;振荡器调制器时间;同步;异步;虚值反复迭代代数Clifford代数； Fermion代数相对论;狄拉克方程。

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《Cybernetics & Human Knowing》 |2019年第3期|107-160|共54页
作者
Louis H. Kauffman;
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Mathematics Department University of Illinois at Chicago Department of Mechanics and Mathematics Novosibirsk State University Russia;

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4. What Does Emergence in Computer Simulations? Simulation between Epistemological and Ontological Emergence [C] . Alex Schmid Epistemological Perspectives on Simulation Workshop . 2009

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5. Imaginary time quantum Monte Carlo simulations of many fermion systems. [D] . Belyaev, Victor V. 2000

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7. EEG Signal Discrimination using Non-linear Dynamics in the EMD Domain S. M. Shafiul Alam,S. M. Shafiul Alam,Aurangozeb, and Syed TarekShahriar Abstract—An EMD-chaos based approach is proposed todiscriminate EEG signals corresponding to healthy persons,and epileptic patients during seizure-free intervals and seizureattacks. An electroencephalogram (EEG) is first empiricallydecomposed to intrinsic mode functions (IMFs). The nonlineardynamics of these IMFs are quantified in terms of the largestLyapunov exponent (LLE) and correlation dimension (CD).This chaotic analysis in EMD domain is applied to a large groupof EEG signals corresponding to healthy persons as well asepileptic patients (both with and without seizure attacks). It isshown that the values of the obtained LLE and CD exhibitfeatures by which EEG for seizure attacks can be clearlydistinguished from other EEG signals in the EMD domain.Thus, the proposed approach may aid researchers in developingeffective techniques to predict seizure activities. Index Terms—Electroencephalogram (EEG), empiricalmode decomposition (EMD), largest Lyapunov exponent (LLE),correlation dimension (CD), epileptic seizures. The Authors are with the Electrical and Electronic EngineeringDepartment, Bangladesh University of Engineering and Technology,Dhaka-1000, Bangladesh (e-mail: imamul@eee.buet.ac.bd) PDF Cite: S. M. Shafiul Alam,S. M. Shafiul Alam,Aurangozeb, and Syed Tarek Shahriar, "EEG Signal Discrimination using Non-linear Dynamics in the EMD Domain," International Journal of Computer and Electrical Engineering vol. 4, no. 3, pp. 326-330, 2012. PREVIOUS PAPER Perception of Emotions Using Constructive Learningthrough Speech NEXT PAPER Physical Layer Impairments Aware OVPN Connection Selection Mechanisms Copyright © 2008-2013. International Association of Computer Science and Information Technology Press (IACSIT Press) [O] . S. M. Shafiul Alam, Syed TarekShahriar 2012

机译：EEG信号在EMD域S. S. Shafiul Alam，S中的非线性动力学使用非线性动力学。 M. Shafiul Alam，Aurangozeb和Syed Tarekshahriar摘要 - 基于EMD Chaos的方法，提出了对应于健康人的EEG信号，癫痫发作期间的癫痫患者和Seizureattacks。脑电图（EEG）首先被凭经上分解为内在模式功能（IMF）。这些IMF的非线性动力学在最大范围的指数（LLE）和相关尺寸（CD）方面是量化的。本域中的混沌分析应用于与健康人相对应的大型脑电图（Asepileptic患者）（两者都有癫痫发作）。因此，所获得的LLE和CD表展的价值可以从EMD领域的其他EEG信号中清晰地区分脑电图的表达展示。本拟议的方法可以帮助研究人员以预测癫痫发作的癫痫发作技术。索引术语 - 脑电图（EEG），仿真态分解（EMD），最大的Lyapunov指数（LLE），相关维度（CD），癫痫发作。作者与电气电子和电子工程公司，孟加拉国工程和技术大学，孟加拉国达卡 - 1000（电子邮件：imamul@eee.buet.ac.bd）pdf cite：s. m. shafiul Alam，s。 M. Shafiul Alam，Aurangozeb和Syed Tarek Shahriar，“EEG信号歧视在EMD领域的非线性动态，”计算机电气工程卷国际杂志。 4，不。 3，pp。326-330,2012，上一篇论文对情绪的看法，使用建设性的学习言论下一篇论文物理层障碍意识到OVPN连接选择机制版权所有©2008-2013。国际计算机科学与信息技术协会出版社（IACSIT Press）

Paper Computers, Imaginary Values and the Emergence of Fermions

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