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...

Accurate models of Overcurrent (OC) with inverse time relay characteristics play an important role for coordination of power system protection schemes. This paper proposes a new method for modeling OC relays curves. The model is based on fuzzy logic and artificial neural networks. The feed forward multilayer perceptron neural network is used to calculate operating times of OC relays for various...

The purpose of this study is to evaluate the performance analysis of multilayer feed forward neural networks trained with back propagation algorithm & descent gradient Radial basis function network for the pattern classification of hand written curve script. This analysis has been done for handwritten text of three letters and for the individual English vowels. This analysis in the performance ...

A comparative study of artificial neural network (ANN) and multiple regression is made to predict the fat tail weight of Balouchi sheep from birth, weaning and finishing weights. A multilayer feed forward network with back propagation of error learning mechanism was used to predict the sheep body weight. The data (69 records) were randomly divided into two subsets. The first subset is the train...

Data mining is the upcoming research area to solve various problems and classification is one of main problem in the field of data mining. In this paper, we use two classification algorithms J48 (which is java implementation of C4. 5 algorithm) and multilayer perceptron alias MLP (which is a modification of the standard linear perceptron) of the Weka interface. It can be used for testing severa...

This paper discusses the use of multilayer feed forward neural networks for predicting a stock's excess return based on its exposure to various technical and fundamental factors. To demonstrate the effectiveness of the approach a hedged portfolio which consists of equally capitalized long and short positions is constructed and its historical returns are benchmarked against T-bill returns and th...

In this paper, a feed forward spiking neural network is tested with spike train patterns with additional and missing spikes. The network is trained with noisy and distorted patterns with an extension of the ReSuMe learning rule to networks with hidden layers. The results show that the multilayer ReSuMe can reliably learn to discriminate highly distorted patterns spanning over 500 ms.

This paper presents a method of recognition of isolated offline handwritten Devanagari numerals using wavelets and neural network classifier. This method of optical character recognition takes the handwritten numeral image as input. After pre-processing, it is subjected to single level wavelet decomposition using Daubechies-4 wavelet filter. This wavelet decomposition allows viewing the input n...