This paper presents our experiences with the use of feed forward neural networks for piano chord recognition and polyphonic piano music transcription. Our final goal is to build a transcription system that would transcribe polyphonic piano music over the entire piano range. The central part of our system uses neural networks acting as pattern recognisers and extracting notes from the source aud...

Propose a neural-network based size and color invariant character recognition system using feed-forward neural network. Our feed-forward network has two layers. One is input layer and another is output layer. The whole recognition process is divided into four basic steps such as pre-processing, normalization, network establishment and recognition. Pre-processing involves digitization, noise rem...

In this paper‎, ‎steady flow of a third-grade fluid in a porous half‎ space has been considered‎. ‎This problem is a nonlinear two-point‎ boundary value problem (BVP) on semi-infinite interval‎. ‎The‎ solution for this problem is given by a numerical method based on the feed-forward artificial‎ neural network model using radial basis activation functions trained with an interior point method‎. ...

In this paper, we propose a feed-forward neural style transfer network which can transfer unseen arbitrary styles. To do that, first, we extend the fast neural style transfer network proposed by Johnson et al. (2016) so that the network can learn multiple styles at the same time by adding a conditional input. We call this as “a conditional style transfer network”. Next, we add a style condition...

Incremental artificial neural networks grow when they learn and shrink when they forget. Competitive Hebbian learning generates the network structure by addition and removal of cells and links. Thus, no network design phase is necessary. The growing cell structure and the growing neural gas network may replace common feed-forward networks in a lot of classification and interpolation tasks.

; Abstract. In 8] we have shown how to construct a 3{layer recurrent neural network that computes the iteration of the meaning function T P of a given propositional logic program, what corresponds to the computation of the semantics of the program. In this article we deene a notion of approximation for interpretations and prove that there exists a 3{layer feed forward neural network that approx...

Investigation of soil properties like Cation Exchange Capacity (CEC) plays important roles in study of environmental reaserches as the spatial and temporal variability of this property have been led to development of indirect methods in estimation of this soil characteristic. Pedotransfer functions (PTFs) provide an alternative by estimating soil parameters from more readily available soil data...

In this study, we focused on the gait of Parkinson’s disease (PD) and presented a gray box model for it. We tried to present a model for basal ganglia structure in order to generate stride time interval signal in model output for healthy and PD states. Because of feedback role of dopamine neurotransmitter in basal ganglia, this part is modelled by “Elman Network”, which is a neural network stru...

The intrinsic hysteresis behavior of piezoelectric material limits the tracking control accuracy of the actuators. This paper describes a tracking control method for piezoelectric actuators based on the combination of feedforward and feedback loops. The hysteresis of piezoelectric actuators is linearized in feedforward loop with an inverse hysteresis model based on a neural network. The number ...

Motivated by basic ideas from formal concept analysis, we propose two ways to directly encode closure operators on finite sets in a 3-layered feed forward neural network.