This study introduces a method for estimating the model parameters of plucked string instruments using artiicial neural networks (ANN's). The system consists of a preprocessor and an ANN model. The prepro-cessor computes the time-varying harmonics of recorded sounds and this data is fed into the ANN model to implement the nonlinear mapping to the parameter space. The main advantage of this meth...

the jamor purpose of the present research is to predict the total stock market index of tehran stock exchange, using a combined method of wavelet transforms, fuzzy genetics, and neural network in order to predict the active participations of finance market as well as macro decision makers.to do so, first the prediction was made by neural network, then a series of price index was decomposed by w...

Zusammenfassung A neural network which models multi-stable perception is presented. The network consists of sensor and inner neurons. The dynamics is established by a stochastic neuronal dynamics, a formal Hebb-type coupling dynamics and a resource mechanism that corresponds to saturation eeects in perception. From this a system of coupled diierential equations is derived and analyzed. Single s...

In this paper, we present a recurrent neural network model for solving CCR Model in Data Envelopment Analysis (DEA). The proposed neural network model is derived from an unconstrained minimization problem. In the theoretical aspect, it is shown that the proposed neural network is stable in the sense of Lyapunov and globally convergent to the optimal solution of CCR model. The proposed model has...

We propose a pulse neural network that exhibits chaotic pattern alternations among stored patterns as a model of multistable perception, which is reflected in phenomena such as binocular rivalry and perceptual ambiguity. When we regard the mixed state of patterns as a part of each pattern, the durations of the retrieved pattern obey unimodal distributions. We confirmed that no chaotic propertie...

A neural network model of visual motion perception and speed discrimination is presented. The model shows how a distributed population code of speed tuning, that realizes a size–speed correlation, can be derived from the simplest mechanisms whereby activations of multiple spatially short-range filters of different size are transformed into speed-tuned cell responses. These mechanisms use transi...

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...

this paper extends the sequential learning algorithm strategy of two different types of adaptive radial basis function-based (rbf) neural networks, i.e. growing and pruning radial basis function (gap-rbf) and minimal resource allocation network (mran) to cater for on-line identification of non-linear systems. the original sequential learning algorithm is based on the repetitive utilization of s...