Abstract
This paper represents a neural model for multilayer perceptron networks in predicting raga notes. In modeling multilayer perceptrons for time series prediction in musicology, the present algorithm chooses the optimal architecture on the basis of minimum of minimum squared error among one, two and three hidden layered architecture .The study related to a sequence of notes in raga Bhupali. The algorithm measures the performance of the neural network evaluated by the minimum squared error at various time instance of the predicted output.
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© 2012 Springer-Verlag Berlin Heidelberg
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Patra, M., Chakraborty, S., Ghosh, D. (2012). Optimized Neural Architecture for Time Series Prediction Using Raga Notes. In: Ystad, S., Aramaki, M., Kronland-Martinet, R., Jensen, K., Mohanty, S. (eds) Speech, Sound and Music Processing: Embracing Research in India. CMMR FRSM 2011 2011. Lecture Notes in Computer Science, vol 7172. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31980-8_2
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DOI: https://doi.org/10.1007/978-3-642-31980-8_2
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-31979-2
Online ISBN: 978-3-642-31980-8
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