Associative abilities of the neural networks concerning the information coding in the real neural systems are studied. Two models which we adopted are the sparsely coded neural network and the oscillator neural network. We theoretically analyze such models with the replica theory and the theory of the statistical neurodynamics. These theories enable us to describe the states of the systems whic...

Rhythmic neural circuits play an important role in biological systems in particular in motion generation. They can be entrained by sensory feedback to induce rhythmic motion at a natural frequency, leading to energy-efficient motion. In addition, such circuits can even store the entrained rhythmical patterns through connection weights. Inspired by this, we introduce an adaptive discrete-time ne...

In this paper we take a connectionist machine learning approach to the problem of metre perception and learning in musical signals. We present a hybrid network consisting of a nonlinear oscillator network and a recurrent neural network. The oscillator network acts as an entrained resonant filter to the musical signal. It ‘perceives’ metre by resonating to the inherent frequencies within the sig...

1 College of Applied Science, Beijing University of Technology, Beijing 100124, China 2 Key Laboratory of Intelligent Information Processing, Institute of Computing Technology, Chinese Academy of Sciences, Beijing 100190, China 3College of Computer Science and Technology, Beijing University of Technology, Beijing 100124, China {mengyong2007, fmfang}@emails.bjut.edu.cn, {qiaoyuanhua, ljduan}@bju...

in this work, time domain analysis is used to solve adler’s equation in order to obtain the required time, for an oscillator under external injection, reaching the steady-state condition. mathematical approach has been applied to fully describe the transient of frequency acquisition in injection-locked lc and ring oscillators considering their time-varying nature. then, the analysis is verified...

This paper presents a compact architecture for CMOS implementation of a pulse-coded neural network with a current controlled oscillator. A computational style described in this paper mimics a biological neural system using pulsestream signaling and analog summation and multiplication. Synaptic weights are multiplied by employing current mirrors and choosing proper W=L ratios of output transisto...

single-valence electron atoms are an important class of atoms. their oscillator strengths are their important properties. knowing the oscillator strengths one can easity calculate the transition probabilities of the spectral lines and hence the lifetimes of energy levels of most atoms. the oscillator strengths of the spectral lines of most atoms are not knoen with sufficient accuracy due to the...

We propose a dynamically coupled neural oscillator network for image segmentation. Instead of pair-wise coupling, an ensemble of oscillators coupled in a local region is used for grouping. We introduce a set of neighborhoods to generate dynamical coupling structures associated with a specific oscillator. Based on the proximity and similarity principles, two grouping rules are proposed to explic...