Digital Signal Processing

Jyotsna Ogale ¹, Alok Jain ²

Affiliations
1 Department of Electronics and Communication Engineering, Samrat Ashok Technological Institute (Degree College), Vidisha-464001 (M.P.), IN
2 Department of Electronics and Instrumentation Engineering, Samrat Ashok Technological Institute (Degree College), Vidisha-464001 (M.P.), IN

Abstract

In this paper, a new approach to design multiplier-free interpolated finite impulse response digital filter is presented. The approach is based on two step procedure, coefficient rounding and sharpening with no recursion equation. Interpolated finite impulse response approach is a very efficient method for designing sharp transition band filters. With this approach, filter with reduced number of multiplier coefficients is designed that permits efficient hardware implementation. The hardware complexity of the filter can be further reduced by employing rounding and sharpening technique. The prototype filter is formulated as a rounded and sharpened interpolated finite impulse response (R&S IFIR) filter. The prototype filter is then used to design the filter bank. Examples show that without introducing additional delay, the proposed approach provides better performance with reduced computational cost.

Keywords

Interpolated Finite Impulse Response Filter, Filter Bank, Cosine Modulation, Rounding Factor, Sharpening Polynomial.

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Ashutosh Datar ¹, Alok Jain ², Pramod Chandra Sharma ³

Affiliations
1 Department of Biomedical Engineering, Samrat Ashok Technological Institute (Engineering College), Vidisha-464001 (M.P.), IN
2 Department of Electronics & Instrumentation Engineering, Samrat Ashok Technological Institute (Engineering College), Vidisha-464001 (M.P.), IN
3 S.D. Bansal College of Technology, Umaria, Indore-452001 (M.P.), IN

Abstract

ECG signal compression techniques employing multirate filter bank is developed. The proposed method utilizes an optimized prototype filter for designing a nearly-perfect reconstruction cosine modulated filter bank. Frequency band decomposition of ECG signal is obtained by analysis filter bank. Most of the ECG energy is concentrated in lower frequency bands. The decomposed signal coefficients are thresholded, quantized and encoded. LZW and Huffman coding is used for comparing the performance. Only significant coefficients are transmitted, while redundant samples are discarded. Various error measures are computed to ensure the quality and fidelity of reconstructed signal.

Keywords

Near Perfect Reconstruction, Filter Banks, Subband Coding, Compression Ratio.

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