期刊论文详细信息
Journal of Applied & Computational Mathematics
Computation by Intention and Electronic Image of the Brain
article
Resconi G1  Licata I2 
[1] Department of Physics and Mathematics, Catholic University;ISEM, Institute for Scientific Methodology
关键词: Intention;    Neuron;    Electrical circuit;    Scattering matrix;    Transmission matrix;    Impedance matrix;    Multi pendulum system;   
DOI  :  10.4172/2168-9679.1000232
来源: Hilaris Publisher
PDF
【 摘 要 】

Neurons as active unities are connected one with the others by synapses in an electronic way. We arguethat brain is not comparable with digital computer with algorithms because intention as software is introduced as transformation in the neural states without any digital reduction. Any electronic system has voltages and currents sources and complex interconnected impedances. By electronic system and neural network we have different possibilities to introduce Freeman intentional transformation in the brain. One is to use source voltages (sensor) to generate wanted behavior of currents (internal flows of the signals) with the same impedance network. We can also reverse the process: given the behavior of the currents we generate wanted voltages transformation (effectors as muscles) with the same impedance. Another possibility is to change the impedance network (memory) to generate wanted internal current. When intention is transformation of references, geometry changes and also the form ofstraight line (geodesic). Special reference and geometry can be modeled by the electrical power as metric. Different types of brain geometries as hyperbolic geometry of waves and elliptic geometry of stable states are discussed with examples. Because we have waves in brain, Karl Pribram created holographic model of brain that by scattering and transmitted matrix can be joined to electronic model. Mechanical system metrics are implemented in the neural network as electronic network.

【 授权许可】

Unknown   

【 预 览 】
附件列表
Files Size Format View
RO202307140004278ZK.pdf 1842KB PDF download
  文献评价指标  
  下载次数:7次 浏览次数:7次