Title :
Entropy, information, Landauer´s limit and Moore´s law
Author :
Tobin, P. ; Blackledge, J.
Author_Institution :
Sch. of Electr. & Electron. Eng., Dublin Inst. of Technol., Dublin, Ireland
Abstract :
In this paper we explore the link between information and entropy by considering the infamous Maxwell demon thought experiment. A non-rigorous mathematical solution by Leo Szilard established this link for the first time, as did Claude Shannon nineteen years later. In 1961, Rolf Landauer´s mathematical solution resulted in the Landauer limit, which is still being hotly debated, but here we discuss the implication of this limit on Moore´s law and future growth in computing power. A workaround the limit is proposed using an Analogue Artificial Neural Network (AANN). Here, we mimic the action of a human brain synapse formed from memristance connected between two Fitzhugh-Nagumo (FN) neuron models. All designs were simulated in Orcad PSpice© version 16.5, but a master-slave synapse was built, tested and outputs compared to simulation results. The synapse was also connected in a star-type network which displayed chaotic-type behaviour for certain parameter values.
Keywords :
brain; entropy; neural nets; AANN; Fitzhugh-Nagumo neuron models; Landauer limit; Moore law; Orcad PSpice version 16.5; analogue artificial neural network; computing power; entropy; human brain synapse; infamous Maxwell demon; information; master-slave synapse; memristance; nonrigorous mathematical solution; Entropy; Fitzhugh-Nagumo model; Landauer limit; Maxwell´s demon; Moore´s law; Orcad PSpice; analogue artificial neural networks; information; memristance; synapse;
Conference_Titel :
Irish Signals & Systems Conference 2014 and 2014 China-Ireland International Conference on Information and Communications Technologies (ISSC 2014/CIICT 2014). 25th IET
Conference_Location :
Limerick
DOI :
10.1049/cp.2014.0716