Kazuki Nakada

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This paper proposes a neuromorphic analog CMOS controller for interlimb coordination in quadruped locomotion. Animal locomotion, such as walking, running, swimming, and flying, is based on periodic rhythmic movements. These rhythmic movements are driven by the biological neural network, called the central pattern generator (CPG). In recent years, many(More)
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(More)
—This paper proposes an analog CMOS circuit that implements a central pattern generator (CPG) for locomotion control in a quadruped walking robot. Our circuit is based on an affine transformation of a reaction-diffusion cellular neural network (CNN), and uses differential pairs with multiple-input floating-gate (MIFG) MOS transistors to implement both the(More)
The present paper addresses burst synchronization in out of phase observed in two pulse-coupled resonate-and-fire neuron (RFN) circuits. The RFN circuit is a silicon spiking neuron that has second-order membrane dynamics and exhibits fast subthreshold oscillation of membrane potential. Due to such dynamics, the behavior of the RFN circuit is sensitive to(More)
We propose an analog current-mode subthreshold CMOS circuit implementing a neuromorphic oscillator. Our circuit is based on the half-center oscillator model proposed by Matsuoka, well known as a building block for constructing a neuromorphic robot locomotion controller. We modified the Matsuoka's oscillator to be suitable for analog curent-mode(More)
We propose an analog CMOS circuit that implements a class of cellular neural networks (CNNs) for locomotion control in robotics. Our circuit is constructed using multiple-input floating-gate MOS (FGMOS) FETs aiming at the voltage-mode operation, and it can be expected to reduce power consumption. Furthermore, we fabricated a prototype chip using a standard(More)
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. From a viewpoint of the phase(More)