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Prediction of Sound Insulation of Sandwich Partition Panels by Means of Artificial Neural Networks

Garg N., Dhruw S., Gandhi L.

Archives of Acoustics

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2017

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Vol. 42, No. 4

643--651

EN

The paper presents the application of Artificial Neural Networks (ANN) in predicting sound insulation through multi-layered sandwich gypsum partition panels. The objective of the work is to develop an Artificial Neural Network (ANN) model to estimate the Rw and STC value of sandwich gypsum constructions. The experimental results reported by National Research Council, Canada for Gypsum board walls (Halliwell et al., 1998) were utilized to develop the model. A multilayer feed-forward approach comprising of 13 input parameters was developed for predicting the Rw and STC value of sandwich gypsum constructions. The Levenberg-Marquardt optimization technique has been used to update the weights in back-propagation algorithm. The presented approach could be very useful for design and optimization of acoustic performance of new sandwich partition panels providing higher sound insulation. The developed ANN model shows a prediction error of ± 3 dB or points with a confidence level higher than 95%.

2

Technical Notes : Practical Concerns Associated with Single-Number Ratings in Measuring Sound Transmission Loss Properties of Partition Panels

Garg N., Kumar A., Maji S.

Archives of Acoustics

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2013

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Vol. 38, No. 1

115--124

EN

The paper presents an extensive review investigating the practical aspects related to the use of single- number ratings used in describing the sound insulation performance of partition wall panels and practical complications encountered in precise measurements in extensive frequency range from 50 Hz to 5 kHz. SWOT analysis of various single number ratings is described. A laboratory investigation on a double wall partition panel combination revealed the significant dependence of STC rating on transmission loss at 125 Hz attributed to 8 dB rule. An investigation conducted on devising alternative spectrums of aircraft noise, traffic noise, vehicular horn noise and elevated metro train noise as an extension to ISO 717-1 Ctr for ascertaining the sound insulation properties of materials exclusively towards these noise sources revealed that the single-number rating Rw + Ctr calculated using ISO 717-1 Ctr gives the minimum sound insulation, when compared with Rw + Cx calculated using the alternative spectrums of aircraft noise, traffic noise, etc., which means that material provides a higher sound insulation to the other noise sources. It is also observed that spectrum adaptation term Cx calculated using the spectrum of noise sources having high sound pressure levels in lower frequencies decreases as compared to ISO 717-1 Ctr owing to significant dependence of Ctr at lower frequencies.

3

Data Compressor for VQ Index Tables

Lu T.-C., Chang C. C.

Fundamenta Informaticae

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2005

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Vol. 65, nr 4

353--371

EN

The vector quantization (VQ) compression scheme has been well accepted as an efficient image compression technique. However, the compression bit rate of the VQ scheme is limited. In order to improve its efficiency, in this paper, we shall propose a new lossless data compression scheme to further condense the VQ index table. The proposed scheme exploits the inter-block correlations in the index table to re-encode the indices. Unlike the well known existing re-encoding schemes such as SOC and STC, the proposed scheme uses a smaller number of compression codes to encode every index that coincides with another on the predefined path. Compared with VQ, SOC and STC, the proposed scheme performs better in terms of compression bit rate.