Physical Implementation of Reservoir Computing through Electrochemical Reaction.

Nonlinear dynamical systems serving reservoir computing enrich the physical implementation of computing systems. A method for building physical reservoirs from electrochemical reactions is provided, and the potential of chemical dynamics as computing resources is shown. The essence of signal processing in such systems includes various degrees of ionic currents which pass through the solution as well as the electrochemical current detected based on a multiway data acquisition system to achieve switchable and parallel testing.

Long- and Short-Term Conductance Control of Artificial Polymer Wire Synapses.

Networks in the human brain are extremely complex and sophisticated. The abstract model of the human brain has been used in software development, specifically in artificial intelligence. Despite the remarkable outcomes achieved using artificial intelligence, the approach consumes a huge amount of computational resources.

A molecular neuromorphic network device consisting of single-walled carbon nanotubes complexed with polyoxometalate.

In contrast to AI hardware, neuromorphic hardware is based on neuroscience, wherein constructing both spiking neurons and their dense and complex networks is essential to obtain intelligent abilities. However, the integration density of present neuromorphic devices is much less than that of human brains. In this report, we present molecular neuromorphic devices, composed of a dynamic and extremely dense network of single-walled carbon nanotubes (SWNTs) complexed with polyoxometalate (POM).

Dynamical system design for silicon neurons using phase reduction approach.

In the present paper, we apply a computer-aided phase reduction approach to dynamical system design for silicon neurons (SiNs). Firstly, we briefly review the dynamical system design for SiNs. Secondly, we summarize the phase response properties of circuit models of previous SiNs to clarify design criteria in our approach.

Active Brownian motion in threshold distribution of a Coulomb blockade model.

Randomly distributed offset charges affect the nonlinear current-voltage property via the fluctuation of the threshold voltage above which the current flows in an array of a Coulomb blockade (CB). We analytically derive the distribution of the threshold voltage for a model of one-dimensional locally coupled CB arrays and propose a general relationship between conductance and distribution. In addition, we show that the distribution for a long array is equivalent to the distribution of the number of upward steps for aligned objects of different heights.

Effect of overglazed and polished surface finishes on the compressive fracture strength of machinable ceramic materials.

Controversy prevails over the effect of overglazing on the fracture strength of ceramic materials. Therefore, the effects of different surface finishes on the compressive fracture strength of machinable ceramic materials were investigated in this study. Plates prepared from four commercial brands of ceramic materials were either surface-polished or overglazed (n=10 per ceramic material for each surface finish), and bonded to flat surfaces of human dentin using a resin cement.

Analog VLSI implementation of resonate-and-fire neuron.

We propose an analog integrated circuit that implements a resonate-and-fire neuron (RFN) model based on the Lotka-Volterra (LV) system. The RFN model is a spiking neuron model that has second-order membrane dynamics, and thus exhibits fast damped subthreshold oscillation, resulting in the coincidence detection, frequency preference, and post-inhibitory rebound. The RFN circuit has been derived from the LV system to mimic such dynamical behavior of the RFN model.

A majority-logic nanodevice using a balanced pair of single-electron boxes.

This paper describes a majority-logic gate device that will be useful in developing single-electron integrated circuits. The gate device consists of two identical single-electron boxes combined to form a balanced pair. It accepts three inputs and produces a majority-logic output by using imbalances caused by the input signals; it produces a 1 output if two or three inputs are 1, and a 0 output if two or three inputs are 0.