Supriya Dhabal

Work place: Netaji Subhash Engineering College Kolkata, West Bengal, India

E-mail: sdhabal@ieee.org

Website:

Research Interests: Engineering, Computational Engineering

Biography

Supriya Dhabal received the B. Tech degree in Electronics and Communication Engineering from Kalyani Govt. Engineering College, Kolkata, West Bengal, India in 2006 and ME degree in Electronics and Tele-Communication Engineering from Jadavpur University of Kolkata, West Bengal, India in 2008.

Author Articles
Efficient Cosine Modulated Filter Bank using Multiplierless Masking Filter and Representation of Prototype Filter Coefficients Using CSD

By Supriya Dhabal Palaniandavar Venkateswaran

DOI: https://doi.org/10.5815/ijigsp.2012.10.04, Pub. Date: 28 Sep. 2012

This paper presents a design of low complexity multichannel Nearly Perfect Reconstruction (NPR) Cosine Modulated Filter Bank (CMFB). CMFBs are used extensively because of ease realization and the inherent advantage of high stop-band attenuation. But, when the number of channel becomes large, it leads to certain limitations as it would require large number of filter coefficients to be optimized and hence longer CPU time; e.g. 32-band or 64-band CMFB. Large number of filter coefficients would also mean that computational complexity of the prototype filter is extremely increased that tends to slow down the convergence to best possible solution. Here, the prototype filter is designed using modified Interpolated Finite Impulse Response (IFIR) technique where masking filter is replaced by multiplier free cascaded structure and coefficients of model filter are converted to nearest Canonical Signed Digit (CSD). The interpolation factor is chosen in such a way that computational cost of the overall filter and different error parameters are reduced. The proposed approach thus leads to reduction in stop-band energy as well as high Side-Lobe-Fall-off-Rate (SLFOR). Three examples have been included to demonstrate the effectiveness of the proposed technique over the existing design methods and savings in computational complexity is also highlighted.

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